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IEEE Transactions on Robotics (T-RO)

T-ro  jcr impact factor 9.4 in 2023.

  To submit your paper, go to the RA-L PaperCept site  ras.papercept.net/journals/ral

-  ICRA@40 :    September 1, 2023 to June 30, 2024

The IEEE Transactions on Robotics (T-RO)  publishes research papers that represent major advances in the state-of-the-art in all areas of robotics. The Transactions welcomes original papers that report on any combination of theory, design, experimental studies, analysis, algorithms, and integration and application case studies involving all aspects of robotics. You can learn more about T-RO's scope, paper length policy, open access option, and preparation of papers for submission at the  Information for Authors page .

As of late May 2020, T-RO no longer has a "short paper" category for new submissions.  Papers that are short may still be published, but they are treated as Regular paper submissions, and they are subject to the same standards for significance.  Authors of short papers (8 pages or fewer) may consider our sister journal, the  IEEE Robotics and Automation Letters  (RA-L).

Table of Contents of the latest T-RO issue ( IEEE Xplore ) Early Access Articles Most Downloaded Articles Special Collections

Joining the Transactions on Robotics Editorial Board

Presenting your transactions on robotics paper at icra, iros, and case.

Any IEEE Transactions on Robotics (T-RO) paper, other than communication items and survey papers, may be presented at either an upcoming IEEE International Conference on Robotics and Automation (ICRA), an upcoming IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), or International Conference On Automation Science and Engineering (CASE), provided most of the key ideas of the paper have never appeared at a conference with a published proceedings (i.e., the paper is a "new" paper and not the evolved version of a previous conference paper or papers). For conference eligibility deadlines, see the RAS conference dates in the blue box above.

Authors may not request any acceleration or delay of the review process based on these criteria.

Upon final notification of acceptance, eligible papers will be offered an option to present at conference in the author's workspace within the PaperCept platform. The prompt within the workspace will include an option to transfer the paper directly to conference organizers. Authors will have a window of one month to select and accept which conference they will present at. Authors are expected to pay the conference fee. Eligible papers may only be presented at one conference.

Historically papers in the Transactions on Robotics have been either "evolutionary" papers (papers extended, with new results, from previously presented conference papers by the same authors) or "new" direct-to-journal papers (papers that are not evolved from conference papers).  Since the introduction of the Robotics and Automation Letters (RA-L), the robotics community has demonstrated strong support for direct-to-journal papers (maximum of eight pages) with the possibility of presentation at a conference.

This IEEE RAS policy, adopted by AdCom in September 2017 and formalizing pilots of the policy at ICRA 2017 and 2018, provides a conference presentation option for "new" direct-to-journal T-RO papers.  Authors are no longer forced to write two versions of the paper (a short one for conference presentation and a longer one for the "final" journal version) if they want the work both to be presented at a conference and to appear in a journal.  This saves on author and reviewer effort, eliminates the confusion over which paper to cite, and reduces the stress on authors and reviewers arising due to submission deadlines for ICRA, IROS, or CASE. The new policy gives a new benefit to T-RO authors and brings high-quality T-RO papers to ICRA, IROS, or CASE without harming the traditional evolutionary model.

Is My Paper "Evolved" or "New?"

This initiative distinguishes between papers that have evolved directly from conference papers ("evolved" papers) and papers that have not ("new" direct-to-journal papers).  Of course the distinction is not always clear-cut, since almost all of one's research has evolved in some way from one's previous papers.

Below are some criteria to consider in the judgment of whether a paper is evolved or new.  If the answer to one or more of these questions is "yes," this is a good sign that your paper should be considered to be evolved.

• Does the journal paper have the same title as the previous conference paper?
• Is there a direct lineage from the conference paper(s) to the journal paper?
• Typically a paper has one or a small number of key new ideas.  (There may be many supporting details.)  Does a majority of the key ideas in the T-RO paper appear in the previous conference paper(s)?
• Would the T-RO paper have been rejected without the content of the previous conference paper(s)?
• Does the T-RO paper use a significant amount of text, results, data, or figures from the previous conference paper(s)?

An advantage of having your paper be considered "evolved" is that you are free to incorporate much of the material from your conference paper(s) without penalty in the review process, provided the new paper provides a significant contribution beyond the conference paper(s) (see the guidance here for more details).  The disadvantage is that your "evolved" paper is not eligible for presentation at ICRA, IROS, or CASE.  The disadvantage of declaring your paper "new" is that you cannot reuse significant portions of the material from your conference paper(s), but the advantage is that the new paper (if accepted) is eligible for presentation at ICRA, IROS, or CASE.

Note that no submission can be considered to be "evolved" from a paper that previously appeared in a journal (including the IEEE Robotics and Automation Letters).

If you are in doubt, send your brief analysis along with the T-RO paper and the relevant conference paper(s) to the Editor-in-Chief for an evaluation.  It is unethical to withhold relevant previous conference paper(s) in this analysis.

IEEE Transactions on Robotics King-Sun Fu Memorial Best Paper Award

2023:  " RACER: Rapid Collaborative Exploration with a Decentralized Multi-UAV System "   by Boyu Zhou, Hao Xu, and Shaojie Shen   vol. 39, no. 3, pp. 1816-1835, June 2023, [ Xplore Link ]

Honorable Mention

"Global Planning for Contact-Rich Manipulation via Local Smoothing of Quasi-dynamic Contact Models" [ Xplore Link ]

"Grasp it Like a Pro 2.0: A Data-Driven Approach Exploiting Basic Shapes Decomposition and Human Data for Grasping Unknown Objects" [ Xplore Link ]

"Kinegami: Algorithmic Design of Compliant Kinematic Chains from Tubular Origami" [ Xplore Link ]

"ANYexo 2.0: A Fully-Actuated Upper-Limb Exoskeleton for Manipulation and Joint-Oriented Training in all Stages of Rehabilitation" [ Xplore Link ]

"Perceptive Locomotion through Nonlinear Model Predictive Control" [ Xplore Link ]

2022:  " Kimera-Multi: Robust, Distributed, Dense Metric-Semantic SLAM for Multi-Robot Systems "   by Yulun Tian; Yun Chang; Fernando Herrera Arias; Carlos Nieto-Granda; Jonathan P. How; Luca Carlone   vol. 38, no. 4, pp. 2022-2038, August 2022, [ Xplore Link ]

"Stabilization of Complementarity Systems via Contact-Aware Controllers"   [ Xplore Link ]

"Autonomous Cave Surveying With an Aerial Robot"   [ Xplore Link ]

"Prehensile Manipulation Planning: Modeling, Algorithms and Implementation"   [ Xplore Link ]

"Rock-and-Walk Manipulation: Object Locomotion by Passive Rolling Dynamics and Periodic Active Control"   [ Xplore Link ]

        "Origami-Inspired Soft Actuators for Stimulus Perception and Crawling Robot Applications"   [ Xplore Link ]

2021:  " Collision Resilient Insect-scale Soft-actuated Aerial Robots With High Agility "   by YuFeng Chen; Siyi Xu; Zhijian Ren; Pakpong Chirarattananon   vol. 37, no. 5, pp. 1752-1764, October 2021, [ Xplore Link ]

"A Backdrivable Kinematically Redundant (6+3)-dof Hybrid Parallel Robot for Intuitive Sensorless Physical Human-Robot Interaction"   [ Xplore Link ]

"Stochastic Dynamic Games in Belief Space"   [ Xplore Link ]

"ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM"   [ Xplore Link ]

"Active Interaction Force Control for Contact-Based Inspection with a Fully Actuated Aerial Vehicle"   [ Xplore Link ]

        "Distributed Certifiably Correct Pose-Graph Optimization"   [ Xplore Link ]

2020: "TossingBot: Learning to Throw Arbitrary Objects With Residual Physics"   by Andy Zeng; Shuran Song; Johnny Lee; Alberto Rodriguez; Thomas Funkhouser vol. 36, no. 4, pp. 1307-1319, August 2020, [ Xplore Link ]

"Design and Validation of a Powered Knee-Ankle Prosthesis With High-Torque, Low-Impedance Actuators" [ Xplore Link ]

"Quantifying Hypothesis Space Misspecification in Learning From Human-Robot Demonstrations and Physical Corrections" [ Xplore Link ]

"Teach-Repeat-Replan: A Complete and Robust System for Aggressive Flight in Complex Environments"    [ Xplore Link ]

"Deep Drone Racing: From Simulation to Reality With Domain Randomization"    [ Xplore Link ]

2019: "Active Learning of Dynamics for Data-Driven Control Using Koopman Operators"   by Ian Abraham and Todd D. Murphey   vol. 35, no. 5, pp. 1071-1083, October 2019, [ Xplore Link ]

2018: "Grasping Without Squeezing: Design and Modeling of Shear-Activated Grippers"   by Elliot Wright Hawkes, Hao Jiang, David L. Christensen, Amy K. Han, and Mark R. Cutkosky   vol. 34, no. 2, pp. 303-316, April 2018, [ Xplore Link ]

"Exploiting Elastic Energy Storage for “Blind” Cyclic Manipulation: Modeling, Stability Analysis, Control, and Experiments for Dribbling"   [ Xplore Link ]

"VINS-Mono: A Robust and Versatile Monocular Visual-Inertial State Estimator"  [ Xplore Link ]

2017: "On-Manifold Preintegration for Real-Time Visual-Inertial Odometry"   by Christian Forster, Luca Carlone, Frank Dellaert, and Davide Scaramuzza   vol. 33, no. 1, pp. 1-21, February 2017, [ Xplore Link ]

2016: "Rapidly Exploring Random Cycles: Persistent Estimation of Spatiotemporal Fields With Multiple Sensing Robots"   by Xiaodong Lan and Mac Schwager   vol. 32, no. 5, pp. 1230-1244, October 2016, [ Xplore Link ]

2015:  " ORB-SLAM: A Versatile and Accurate Monocular SLAM System" by  Raul Mur-Artal, J. M. M. Montiel and Juan D. Tardos vol. 31, no. 5, pp. 1147-1163, 2015 [ Xplore Link ].

2014:  " Catching Objects in Flight" by  Seungsu Kim, Ashwini Shukla, Aude Billard vol. 30, no. 5, pp. 1049-1065, 2014 [ Xplore Link ].

2013: " Robots Driven by Compliant Actuators: Optimal Control under Actuation Constraints" by  David J. Braun, Florian Petit, Felix Huber, Sami Haddadin, Patrick van der Smagt, Alin Albu-Schäffer, Sethu Vijayakumar vol. 29, no. 5, pp. 1085-1101, 2013 [ Xplore Link ].

2012: " Reinforcement Learning With Sequences of Motion Primitives for Robust Manipulation" by  Freek Stulp, Evangelos A. Theodorou, Stefan Schaal vol. 28, no. 6, pp. 1360-1370, 2012 [ Xplore Link ].

2011: " Human-Like Adaptation of Force and Impedance in Stable and Unstable Interactions" by  Chenguang Yang, Gowrishankar Ganesh, Sami Haddadin, Sven Parusel, Alin Albu-Schaeffer, Etienne Burdet vol. 27, no. 5, pp. 918-930, 2011 [ Xplore Link ].

2010: " Design and Control of Concentric-Tube Robots" by  Pierre E. Dupont, Jesse Lock, Brandon Itkowitz, Evan Butler vol. 26, no. 2, pp. 209-225, 2010 [ Xplore Link ].

2009: " Vision-Aided Inertial Navigation for Spacecraft Entry, Descent, and Landing" by  Anastasios I. Mourikis, Nikolas Trawny, Stergios I. Roumeliotis, Andrew E. Johnson, Adnan Ansar, Larry Matthies vol. 25, no, 2, pp. 264-280, 2009 [ Xplore Link ].

2008: " Smooth Vertical Surface Climbing with Directional Adhesion" by  Sangbae Kim, Matthew Spenko, Salomon Trujillo, Barrett Heyneman, Daniel Santos, Mark R. Cutkosky vol. 24, no. 1, pp. 65-74, 2008 [ Xplore Link ].

2007: " Manipulation Planning for Deformable Linear Objects" by  Mitul Saha, Pekka Isto vol. 23, no. 6, pp. 1141-1150, 2007 [ Xplore Link ].

2006: " Exactly Sparse Delayed-State Filters for View-Based SLAM" by  Ryan M. Eustice, Hanumant Singh, John J. Leonard vol. 22, no. 6, pp. 1100-1114, 2006 [ Xplore Link ].

2005: " Active Filtering of Physiological Motion in Robotized Surgery Using Predictive Control" by  Romuald Ginhoux, Jacques Gangloff, Michel de Mathelin,Luc Soler, Mara M. Arenas Sanchez, Jacques Marescaux vol. 21, no. 1, pp. 67-79, 2005 [ Xplore Link ].

2004: " Reactive Path Deformation for Nonholonomic Mobile Robots" by  Florent Lamiraux, David Bonnafous, Olivier Lefebvre vol. 20, no. 6, pp. 967-977, 2004 [ Xplore Link ].

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IEEE/CAA Journal of Automatica Sinica

• JCR Impact Factor: 15.3 , Top 1 (SCI Q1) CiteScore: 23.5 , Top 2% (Q1) Google Scholar h5-index: 77， TOP 5

Mohammadhossein Ghahramani, Yan Qiao, MengChu Zhou, Adrian O’Hagan and James Sweeney, "AI-Based Modeling and Data-Driven Evaluation for Smart Manufacturing Processes," , vol. 7, no. 4, pp. 1026-1037, July 2020. doi:

Mohammadhossein Ghahramani, Yan Qiao, MengChu Zhou, Adrian O’Hagan and James Sweeney, "AI-Based Modeling and Data-Driven Evaluation for Smart Manufacturing Processes," , vol. 7, no. 4, pp. 1026-1037, July 2020. doi:

AI-Based Modeling and Data-Driven Evaluation for Smart Manufacturing Processes

Doi:  10.1109/jas.2020.1003114.

• Mohammadhossein Ghahramani , 
• Yan Qiao , 
• MengChu Zhou ,  , 
• Adrian O’Hagan , 
• James Sweeney

Mohammadhossein Ghahramani (S’15–M’18) obtained the B.S. and M.S. degrees in information technology engineering from Amirkabir University of Technology-Tehran Polytechnic, Iran, and the Ph.D. degree in computer technology and application from Macau University of Science and Technology in 2018. He was a Technical Manager and Senior Data Analyst of the Information Centre of Institute for Research in Fundamental Sciences from 2008 to 2014. He is currently a Post-Doctoral Research Fellow at University College Dublin (UCD), Ireland. He is also a Member of the Insight Centre for Data Analytics at UCD. His research interests include smart cities, machine learning, artificial intelligence, internet of things, and big data. Dr. Ghahramani was a Recipient of the Best Student Paper Award of 2018 IEEE International Conference on Networking, Sensing and Control . He has served as a Reviewer of over 10 journals including IEEE Transactions on Cybernetics, IEEE Transactions on Neural Networks and Learning Systems, and IEEE Transactions on Industrial Informatics

Yan Qiao (M’16) received the B.S. and Ph.D. degrees in industrial engineering and mechanical engineering from Guangdong University of Technology in 2009 and 2015, respectively. From Sept. 2014 to Sept. 2015, he was a Visiting Student with the Department of Electrical and Computer Engineering, New Jersey Institute of Technology, USA. From Jan. 2016 to Dec. 2017, he was a Post-Doctoral Research Associate with the Institute of Systems Engineering, Macau University of Science and Technology. Since Jan. 2018, he is an Assistant Professor with the Institute of Systems Engineering, Macau University of Science and Technology. He has over 60 publications, including one book chapter and over 30 international journal papers. His research interests include discrete event systems, production planning, Petri nets, scheduling, and control. Dr. Qiao was a Recipient of the QSI Best Application Paper Award Finalist of 2011 IEEE International Conference on Automation Science and Engineering , the Best Student Paper Award of 2012 IEEE International Conference on Networking, Sensing and Control , and the Best Conference Paper Award Finalist of 2016 IEEE International Conference on Automation Science and Engineering . He has served as a Reviewer for a number of journals

MengChu Zhou (S’88–M’90–SM’93–F’03) received the B.S. degree in control engineering from Nanjing University of Science and Technology in 1983, the M.S. degree in automatic control from Beijing Institute of Technology in 1986, and the Ph. D. degree in computer and systems engineering from Rensselaer Polytechnic Institute, USA, in 1990. He joined New Jersey Institute of Technology (NJIT), USA, in 1990, and is now a Distinguished Professor of electrical and computer engineering. His research interests include Petri nets, intelligent automation, internet of things (IOT), big data, web services, and intelligent transportation. He has over 800 publications including 12 books, over 500 journal papers (over 400 in IEEE transactions), 12 patents and 29 book-chapters. He is the founding Editor of IEEE Press Book Series on Systems Science and Engineering and Editor-in-Chief of IEEE/CAA Journal of Automatica Sinic a. He is a Recipient of Humboldt Research Award for US Senior Scientists from Alexander von Humboldt Foundation, Franklin V. Taylor Memorial Award and the Norbert Wiener Award from IEEE Systems, Man and Cybernetics Society . He is a Life Member of the Chinese Association for Science and Technology-USA and served as its President in 1999. He is a Fellow of International Federation of Automatic Control (IFAC), American Association for the Advancement of Science (AAAS) and Chinese Association of Automation (CAA)

Adrian O’Hagan is a Lecturer and Researcher in statistics and actuarial science at University College Dublin (UCD), Ireland. He holds the degree in actuarial science and the M.Sc. and Ph.D. degrees in statistics from UCD. He uses cutting edge statistical and data analytics techniques to solve real industrial problems in modelling and pricing risk, working with leading insurers and financial institutions. He currently supervises Ph.D. students in statistical genetics with actuarial applications and statistics and actuarial science, and is currently expanding his research group in the FinTech space. He serves as an Examiner for the Institute and faculty of Actuaries and is a Referee for several leading statistics journals

James Sweeney is a Lecturer and Researcher in statistics at the Royal College of Surgeons Ireland (RCSI), Ireland, with the Ph.D. degree in statistical climatology. His research interests range across the fields of spatial analysis, high performance computing and simulation, and statistical applications in medicine and agriculture. Dr. Sweeney’s core strengths are in the analysis of extremely large datasets, particularly those comprised of multivariate, spatially indexed data with practical applications including the modelling of house price information in Dublin, as well as evaluating the speed and cost of abrupt climate change

• Corresponding author: M. C. Zhou is with the Helen and John C. Hartmann Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ 07102 USA (e-mail: [email protected] )
• Revised Date: 2020-02-22
• Accepted Date: 2020-03-06
• Artificial intelligence (AI) , 
• cyber physical systems , 
• feature selection , 
• genetic algorithms (GA) , 
• industrial internet of things (IIOT) , 
• machine learning , 
• neural network (NN) , 
• smart manufacturing

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[5]	, , : , vol. 44, pp. 318–326, 2014. doi:
[6]	, vol. 4, pp. 27–40, 2017. doi:
[7]	, 2020. doi:
[8]	, vol. 88, pp. 16–27, Nov. 2018.
[9]	, vol. 20, pp. 1031–1041, 2019. doi:
[10]	, vol. 16, pp. 351–362, 2019. doi:
[11]	, vol. 4, pp. 6–18, 2017. doi:
[12]	, vol. 6, no. 1, pp. 1–31, Jan. 2019. doi:
[13]	, vol. 62, pp. 3768–3774, 2015.
[14]	, vol. 46, pp. 1551–1565, 2016. doi:
[15]	, vol. 13, pp. 2039–2047, 2017. doi:
[16]	, vol. 47, pp. 1263–1272, 2017. doi:
[17]	, Seattle, USA, 2008, DOI: .
[18]	, vol. 19, pp. 159–172, 2006. doi:
[19]	, pp. 3355–3371, 2013.
[20]	, vol. 20, no. 4, pp. 345–354, 2007. doi:
[21]	, vol. 24, no. 1, pp. 59–68, 2011. doi:
[22]	, vol. 25, no. 3, pp. 373–383, 2012. doi:
[23]	, vol. 28, no. 3, pp. 318–328, 2015. doi:
[24]	, Macau, pp. 298–310, 2014.
[25]	, vol. 30, pp. 135–142, May 2017. doi:
[26]	, vol. 49, 2019.
[27]	, vol. 20, pp. 606–626, 2016. doi:
[28]	, Berlin, Germany, 2009.
[29]	, USA, 2006, pp. 1–8.
[30]	, vol. 47, pp. 2193–2202, 2017. doi:
[31]	, , , ( )
[32]	, vol. 6, no. 3, pp. 703–715, May 2019. doi:
[33]	, vol. 47, no. 12, pp. 4263–4274, Dec. 2018.
[34]	, vol. 36, pp. 1–21, 2011.
[35]	, vol. 48, 2018.
[36]	, vol. 49, pp. 1652–1665, 2017.
[37]	, vol. 44, pp. 793–804, 2013.
[38]	& , vol. 40, no. 1, pp. 16–28, 2014.
[39]	, vol. 15, no. 4, pp. 2456–2468, Apr. 2019.
[40]	, vol. 16, no. 3, pp. 1137–1147, Jul. 2019.
[41]	, , : , vol. 49, no. 12, pp. 2416–2423, Dec. 2019.
[42]	, vol. 6, no. 3, pp. 838–849, May 2019.
[43]	, vol. 6, no. 5, pp. 1240–1250, Sept. 2019.
[44]	, vol. 50, no. 1, pp. 233–246, Jan. 2020.
[45]	, vol. 21, no. 1, pp. 362–373, Jan. 2020.
[46]	, vol. 17, no. 1, pp. 166–176, Jan. 2020.
[47]	, vol. 17, no. 2, pp. 621–632, Apr. 2020.
[48]	, vol. 30, no. 2, pp. 601–614, Feb. 2019.
[49]	, vol. 16, no. 2, pp. 729–740, Apr. 2019.
[50]	, vol. 16, no. 4, pp. 1686–1697, Oct. 2019.
[51]	, pp. 11887–11896, 2019.

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通讯作者: 陈斌, [email protected]

沈阳化工大学材料科学与工程学院 沈阳 110142

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• PDF Downloads( 94 )
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• Most work in the area of manufacturing data analysis are based on PCA-based approaches. They are not able to recognize nonlinear relationships among features and extract complex pattern. To address this concern, a dynamic feature selection model based on an integrated algorithm including a meta-heuristic method (GA) and an artificial neural network is proposed. The implemented algorithm considers two major conflicting objectives: minimizing the number of features and maximizing the classification performance. The result of the proposed model has been compared with traditional approaches.
• The proposed AI-based multi-objective feature selection method together with an efficient classification algorithm can enables decision makers to scrutinize manufacturing processes.
• Copyright © 2022 IEEE/CAA Journal of Automatica Sinica
• 京ICP备14019135号-24
• E-mail: [email protected]  Tel: +86-10-82544459, 10-82544746
• Address: 95 Zhongguancun East Road, Handian District, Beijing 100190, China

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• Figure 1. Different levels of automation and their corresponding data analytics (ERP:= enterprise resource planning; MES:= manufacturing execution systems; SCADA:= supervisory control and data acquisition; HMI:= human machine interface; PLC:= programmable logic controller; CNC:= computer numerical control; RTU:= remote terminal unit).
• Figure 2. Feature selection model using artificial neural network and genetic algorithm
• Figure 3. Reproduction phase.
• Figure 4. Cost function value versus NFE
• Figure 5. ROC curves for different classification methods: (a) linear discriminant; (b) random forest; (c) logistic regression; (d) Gaussian SVM; (e) k-NN; and (f) SVM with RBF kernel
• Figure 6. Selecting features based on a conventional method, i.e., Lasso regression. The panels show the Lasso coefficient estimates and the curve of the measurements for the degrees of freedom of the Lasso
• Figure 7. Comparing ROC results from the (a) proposed method vs (b) PCA vs (c) Lasso regression

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IEEE Robotics & Automation Magazine

Main content, june 2024, vol. 31,  no. 2.

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Columns/Departments

Robots from above: extending our reach [from the editor’s desk], to publish in a journal or a conference [president’s message], the next generation of robotics: the 2023 ieee/rsj international conference on intelligent robots and systems in detroit, mi, usa [conference highlights], what does the hype about humanoids really mean [industry activities], launching queer in robotics [women in engineering], standards update: robot task representation standard and user guide development [standards], how technology alters morality and why it matters [ethics], society news, deadline for ras local chapter initiative grants, 2024 ieee ras award recipients announced, icra @ 40: a special event to commemorate the 40th anniversary of icra and ras.

IEEE Robotics & Automation Magazine   publishes four issues per year: March, June, September and December.

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Real-Time Machine Learning Applications In Mobile Robotics

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Submission Deadline: 31 December 2020

IEEE Access invites manuscript submissions in the area of Real-Time Machine Learning Applications In Mobile Robotics.

In the last ten years, advances in machine learning methods have brought tremendous developments to the field of robotics. The performance in many robotic applications such as robotics grasping, locomotion, human-robot interaction, perception and control of robotic systems, navigation, planning, mapping, and localization has improved since the appearance of modern machine learning methods. In particular, deep learning methods have brought significant improvements in a broad range of robot applications, including drones, mobile robots, robotics manipulators, bipedal robots, and self-driving cars. The availability of big data and more powerful computational resources, such as Graphics Processing Units (GPUs), have made numerous robotics applications feasible that were not possible previously.

Despite recent advances, there are still gaps in applying available machine learning methods to real robots. Directly transferring algorithms that work successfully in the simulation to the real robot and self-learning of robots are among the current challenges. Moreover, there is also a need for new real-time algorithms and more explainable and interpretable models that receive and process data from the sensors such as cameras, Light Detection and Ranging (LIDAR), Inertial Measurement Unit (IMU), and Global Positioning System (GPS), preferably in an unsupervised or semi-supervised fashion.

This Special Section in IEEE Access aims to present the works relating to the design and usage of the real-time machine learning methods on all mobile robots including legged and humanoid platforms, focusing on state-of-the-art methods, such as deep learning, generative adversarial networks, scalable evolutionary algorithms, reinforcement learning, probabilistic graphical models, Bayesian methods, and explainable and interpretable approaches. The Special Section will present original research articles covering the implementations and applications of mobile robots and incorporating up-to-date results, theorems, algorithms, and systems.

The topics of interest include, but are not limited to:

• Robotic learning by simulations
• Learning and adaptive algorithms for robotic mobile manipulators and humanoid robots
• Human-robot interaction, learning from human demonstrations
• Learning for human-robot collaborative tasks
• Autonomous grasping and manipulation by using mobile robots
• Multi-robot systems, networked robots, and robot soccer
• Control, complex action learning, and predictive learning from sensorimotor information for bio-inspired social robots
• Autonomous driving, navigation, planning, mapping, localization, collision avoidance, and exploration
• Robotics and autonomous system design and implementation
• Nonlinear control and visual servoing in robotic systems
• Soft robotics
• Usage of sensors, such as EEG, ECG, and IMU in robotics
• Usage of explainable machine learning and interpretable artificial intelligence in robotics

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility and downloads of articles.

Associate Editor:  Aysegul Ucar, Firat University, Turkey

Guest Editors:

• Jessy W. Grizzle, University of Michigan, USA
• Maani Ghaffari Jadidi, University of Michigan, USA
• Mattias Wahde, Chalmers University of Technology, Sweden
• Levent Akin, Bogazici University, Turkey
• Jacky Baltes, National Taiwan Normal University, Taiwan
• Işıl Bozma, Bogazici University, Turkey
• Jaime Valls Miro, University of Technology Sydney, Australia

Relevant IEEE Access Special Sections:

• Advances in Machine Learning and Cognitive Computing for Industry Applications
• Integrative Computer Vision and Multimedia Analytics
• Uncertainty Quantification in Robotic Applications

IEEE Access Editor-in-Chief:   Prof. Derek Abbott, University of Adelaide

Article submission: Contact Associate Editor and submit manuscript to: http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: [email protected] .

Advanced Communications and Networking Techniques for Wireless Connected Intelligent Robot Swarms

Submission Deadline: 31 May 2020

IEEE Access invites manuscript submissions in the area of Advanced Communications and Networking Techniques for Wireless Connected Intelligent Robot Swarms.

Robot swarm is one of the hottest topics in both robotics and artificial intelligence, and exciting progress is being achieved. As the key enablers in practical robot swarms, communication and networking are attracting attention. Most applications consider centralized control and reliable communication infrastructure, in order to avoid the significantly increased complexity of distributed task allocation, formation control and collision avoidance in robot swarms.

There are many challenges and problems that are yet to be solved in developing real-world applications of wireless connected robot swarms. For example, collaborations of heterogeneous robot swarms need to function reliably and robustly in the absence of communication infrastructures in remote areas or post-disaster rescues. The research of communications and networking for wireless-connected robot swarms demands joint efforts in robotic and communications disciplines. The objective is to develop technologies that enable efficient management of wireless spectrum resources and highly-networked intelligent behaviors to achieve the full potential of wireless-connected robot swarms.

This Special Section in IEEE Access aims to present recent developments in communications and networking for wireless connected intelligent robot swarms, and their applications, as well as to provide a reference for future research of wireless communication and networking, and their integration with autonomous robotics. The contributions of this Special Section will cover a wide range of research and development topics relevant to autonomous robotic design, cognitive communications, cognitive networking and artificial intelligence. We invite submissions of high-quality original technical and survey articles, which have not been published previously, on the analysis, modeling, simulations and field experiments, as well as articles that can fill the gap between theoretical contributions on intelligent swarms and practical demonstrations and applications.

• Channel modeling and simulation for wireless connected robot swarms
• Cognitive PHY and MAC protocol design for wireless connected robot swarms
• Ad hoc networking for wireless connected robot swarms
• Decentralized control and distributed protocol design for wireless connected robot swarms
• Energy scavenging and power transfer techniques for wireless connected robot swarms
• Data-driven optimization of wireless networks for robot swarms
• Joint design of wireless communications and autonomous robot behaviours, e.g. networked control, network-based fault detection and tolerance, path planning, formation control, data sharing without explicit wireless communications etc.
• Testbeds and experimental evaluations for communications and networking in wireless-connected robot swarms
• Field demonstrations and applications of aerial, ground and underwater robotic swarms
• Resource allocation in wireless-connected robot swarms
• Applications of deep learning techniques in wireless connected robot swarms
• Transfer learning and reinforcement learning for networking and communications of robot swarms in complex unknown and unexplored environments
• Maintaining wireless communication-connectivity in wireless-connected robot swarms
• Underwater robotic swarm communications and networking design
• Control algorithm and behavior issues in wireless-connected robot swarms
• Distributed sensing and precise mapping in wireless-connected robot swarms
• Effect of smart sensing technologies on communications in wireless-connected robot swarms
• Control, formation and navigation in wireless-connected robot swarms
• Swarm intelligence in wireless-connected robot swarms
• Cooperative robotic swarms for Internet-of-Things ecosystems

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor:  Jiankang Zhang, University of Southampton, UK

• Bo Zhang, National Innovation Institute of Defense Technology, China
• DaeEun Kim, Yonsei University, Korea
• Hui Cheng, Sun Yat-sen University, China
• Jinming Wen, University of Toronto, Canada
• Luciano Bononi, University of Bologna, Italy
• Venanzio Cichella, University of Iowa, USA
• Networks of Unmanned Aerial Vehicles: Wireless Communications, Applications, Control and Modelling
• Network Resource Management in Flying Ad Hoc Networks: Challenges, Potentials, Future Applications, and Wayforward
• Artificial Intelligence and Cognitive Computing for Communications and Networks

For inquiries regarding this Special Section, please contact: [email protected] .

Performance Evaluation of Multi-UAV System in Post-Disaster Application….

Can eyes in the air counter chaos on the ground? Researchers in Japan analyzed performance of unmanned aerial vehicles (UAVs) used in the response to the 2011 Tohoku earthquake-tsunami disaster, and report on their findings in this IEEE Access article of the week.

The paper proposes an evaluation of unmanned aerial vehicles (UAVs) performance in the mapping of disaster-struck areas. Sendai city in Japan, which was struck by the Tohoku earthquake/tsunami disaster in 2011, was mapped using multi-heterogeneous UAV.

Normal mapping and searching missions are challenging as human resources are limited, and rescue teams are always needed to participate in disaster response mission. Mapping data and UAV performance evaluation will help rescuers to access and commence rescue operations in disaster-affected areas more effectively.

Herein, flight-plan designs are based on the information recorded after the disaster and on the mapping capabilities of the UAVs. The numerical and statistical results of the mapping missions were validated by executing the missions on real-time flight experiments in a simulator and analyzing the flight logs of the UAVs.

After considering many factors and elements that affect the outcomes of the mapping mission, the authors provide a significant amount of useful data relevant to real UAV modules in the market. All flight plans were verified both manually and in a hardware-in-the-loop simulator developed by the authors. Most of the existing simulators support only a single UAV feature and have limited functionalities such as the ability to run different models on multiple UAVs.

The simulator demonstrated the mapping and fine-tuned flight plans on an imported map of the disaster. As revealed in the experiments, the presented results and performance evaluations can effectively distribute different UAV models in post-disaster mapping missions.

View this article n IEEE Xplore

Additive Manufacturing Security

Submission Deadline: 30 April 2020

IEEE Access invites manuscript submissions in the area of Additive Manufacturing Security.

Additive Manufacturing (AM), a.k.a. 3D Printing, is a rapidly growing multi-billion dollar industry. This technology is being used to manufacture 3D objects for a broad range of application scenarios such as prototypes in R&D and functional parts in safety critical systems. The benefits of this technology include shorter design-to-product time, just-in-time and on-demand production, and close proximity to assembly lines. Furthermore, AM can produce functional parts with complex internal structures and optimized physical properties with less material waste than subtractive manufacturing.

Due to the numerous technical and economic advantages that this technology promises, AM is expected to become a dominant manufacturing technology in both industrial and home settings. The need to secure physical and cyber-physical systems gives rise to a corresponding need to understand potential attacks via AM systems, and to develop countermeasures that will enable attack prevention, detection, and digital investigation. So far, three major security threat categories have been identified for AM: theft of technical data (or violation of intellectual property, IP), sabotage of AM, and manufacturing of illegal objects. AM Security is a fairly new and highly multi-disciplinary field of research that addresses these threats.

The aim of this Special Section in IEEE Access is to discuss recent advances in AM Security, addressing both offensive and defensive approaches.

• Compromise of AM systems and environment
• Security threats and attacks in AM context: Theft of technical data (or violation of intellectual property), sabotage of AM, manufacturing of illegal objects
• Technical approaches to detect attacks on/with AM
• Technical approaches to prevent attacks on/with AM
• Digital Investigation and [digital] forensics in the AM context
• Legal aspects of attacks on/with AM
• Economic incentives for AM Security
• Socioeconomic implications of attacks on/with AM
• Comparative analysis of AM vs. CPS/IoT/Industry 4.0/… Securities

Associate Editor:  Mark Yampolskiy, Auburn University, USA

• Mohammad Al Faruque, University of California Irvine, USA
• Raheem Beyah, Georgia Tech, USA
• William Frazier, Naval Air Systems, USA
• Wayne King, The Barnes Group Advisors, USA
• Yuval Elovici, Ben-Gurion University of the Negev, Israel
• Anthony Skjellum, University of Tennessee at Chattanooga, USA
• Joshua Lubell, National Institute of Standards and Technology (NIST), USA
• Celia Paulsen, National Institute of Standards and Technology (NIST), USA
• Cyber-Physical Systems
• Collaboration for Internet of Things
• Towards Service-Centric Internet of Things (IoT): From Modeling to Practice

IEEE Access Editor-in-Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

Paper submission: Contact Associate Editor and submit manuscript to: http://ieee.atyponrex.com/journal/ieee-access

For inquiries regarding this Special Section, please contact: [email protected] .

Cloud-based Robotic Systems for Intelligent Services

Submission Deadline:  1 July 2018

IEEE Access invites manuscript submissions in the area of Cloud-based Robotic Systems for Intelligent Services.

Recent advances in sensor/actuator as well as artificial intelligence (AI) technologies have made it possible for mobile robots such as autonomous automobiles and autonomous unmanned aerial vehicles to go about performing their tasks in varied environments. With wireless communications, these mobile robots can be connected to each other to exchange information, coordinate their movements, and cooperate to perform more extensive tasks, forming robotic systems. Using wireless communications, such robotic systems can further be connected to cloud computing services via the mobile Internet, which offers the potential to significantly enhance the capabilities of such robotic systems. Thus cloud-based robotic systems offer great promises for intelligent services beyond the capabilities of current robots or robotic systems.

First, robot systems employing advanced AI techniques that leverage multiple layer artificial neural networks for deep learning can enable intelligent services that learn from past experience to plan a course of actions that optimizes some task objectives, e.g., minimizing energy consumption, for the current environmental conditions. However, these machine learning techniques are computation intensive and may not be well supported by individual robotic systems. In contrast, cloud computing services offer virtually unlimited computation resources on-demand in a scalable manner, greatly facilitating the use of advanced AI techniques in robotic systems. Second, widespread deployment of robotic systems employing a large number of sensors results in a massive amount of data being generated over short periods of time. Cloud-based big data analytics can be employed to derive useful information to enhance the utility of cloud-based robotic systems. For example, applying big data analytics to data collected from a large number of cloud-based robotic systems, a manufacturer may be able to determine that a batch of sensors manufactured by this company is defective. Third, it is conceivable that in the future distributed general purpose robotic units connected to the cloud can be dynamically configured and programmed to form logical robotic systems under software control to perform specific services in a virtualized manner, i.e., cloud-based robotic systems can provide software-defined robotic system as a service.

Cloud computing platforms would be crucial to enable a programming environment capable of fast service creation, as well as an operational and management environment to ensure that these intelligent robotic services can operate reliably and be properly managed.

Based on the above observations, we can see that cloud-based robotic systems offer great potential for intelligent services in both the short and longer term, but there are many technical challenges that need to be addressed.

Some of the technical challenges and potential applications of cloud-based robotic systems include but are not limited to:

• Cloud-based big data analytics mechanisms;
• Cooperative mechanisms to coordinate the information of robotic systems and share updates on detected changes in the environment;
• Architectures, programming framework, management and control mechanisms to enable robotic function virtualization;
• Robotic edge computing to complement the cloud in satisfying hard real time interaction needs;
• Robot-assisted healthcare, especially for shut-in and elderly patients, with monitoring, diagnostic and simple treatment capabilities; by sampling data from sensors for body to the cloud system, using data mining and machine learning techniques;
• Smart homes, offices and factories equipped with cloud-based robotic systems for enhanced security, energy efficiency, work throughput, occupant comfort, etc.

The main objective of this Special Section in IEEE Access is to collect multidisciplinary research contributions on technological breakthrough and advancement towards cloud-based robotic systems for intelligent services. Topics explored in this Special Section include, but are not limited, to the following aspects of intelligent services involving cloud-based robotic systems:

• Cloud computing technologies
• Cooperative robotic systems
• Multi-modal robotic cognition
• Cooperative communications among robots
• Real-time big data analytics of customers
• Data mining techniques
• Cloud architecture and cloud storage
• Mobile social networks
• Instance detection and recognition in robotic system
• Image and scene classification in robotic system
• Semantic interpretation in robotic system
• Robot function virtualization
• Robotic edge computing

Associate Editor: Prof. Xiping Hu, Chinese Academy of Sciences, China

• Victor C.M. Leung, University of British Columbia, Canada
• Adnan Al-Anbuky, Auckland University of Technology, New Zealand
• Ken Goldberg, University of California, Berkeley, USA
• Hesheng Wang, Shanghai Jiao Tong University, China
• Fei Wang, Cornell University, USA
• Jianwei Zhang, University of Hamburg, German
• Trends and Advances for Ambient Intelligence with Internet of Things Systems
• Big Data Analytics in Internet-of-Things and Cyber-Physical System

Industry 4.0

For inquiries regarding this Special Section, please contact:  [email protected]

Submission Deadline:  20 September 2016

IEEE Access invites manuscript submissions in the area of Industry 4.0.

Industry 4.0 is a recently emerging buzzword that gains significant interest among all stakeholders of the global industry-related R&D market from the academia to worldwide companies. It is a typical business that attracts everyone yet the definitions are not very matured. It is an amazing melting pot of disruptive technologies with easy grip to put it on the flag.

No doubt, to maximize the impact of Industry 4.0, researchers from different fields and industrial people have to work shoulder to shoulder applying the awesome inventions in practice. On the top of the wave, it is timely to analyze who will benefit from the novel achievements and how.

With defining the scope of the Special Section in IEEE Access , we also make an attempt to grasp the main directions within Industry 4.0. Arbitrary mixtures of the following topics are welcome in form of original research, survey or epistemological works.

1. Utilization of the latest mechatronics in manufacturing processes

• Flexible automation, Robotics, Human Machine co-working, autonomous transportation, etc.

2. Extensive data collection and storage

• Continuous measurement and tracking
• Logging and analysis of human activity in production
• Factory-wide monitoring of internal state of industrial controllers
• Storage and organization of the collected data
• Data-driven modelling for design, analysis and prediction

3. Big Data analytics

• Searching for higher order relationship in collected data with various aims.
• Fault forecast
• Identification of bottlenecks
• Identification of surplus capacities
• Detection of Human failures and bad practices

4. Feedback to industrial processes

• Real-time process optimization: scheduling, logistics, etc.
• Optimal maintenance scheduling
• Fast intervention in fault situations

5. Support of human

• New generation of interactive displays: Virtual and Augmented Reality
• Reduction of cognitive load
• Advances toward the augmented human

6. Technology-based support of high added value processes in management and design

• Knowledge representation and user interfaces
• Tools for distributed teamwork
• Virtual teams, virtual enterprise
• Process parameters optimization
• Technologies for building twin model of analysis and design

7. New challenges of security

• Information Privacy, Security and Data Integrity
• Means of vulnerability
• Physical security (Human machine coexistence)

Researchers, engineers and all representatives of academia and industry are encouraged to submit their articles and contribute to the progress of Industry 4.0. This is a very trending topic, since billions of public and private funding are available for industrial innovation naturally related to Industry 4.0.

We also highly recommend the submission of multimedia with each article as it significantly increases the visibility, downloads, and citations of articles.

Associate Editor: Shun-Feng Su, National Taiwan University of Science and Technology, Taiwan

Guest Editors: 1. Imre J. Rudas, Óbuda University, Hungary 2. Jacek M. Zurada, University of Louisville, USA 3. Meng Joo Er, Nanyang Technology University, Singapore 4. Jyh-Horng Chou, National Kaohsiung University of Applied Sciences, Taiwan 5. Daeil Kwon, Ulsan National Institute of Science and Technology, Korea

IEEE Access Editor in Chief: Michael Pecht, Professor and Director, CALCE, University of Maryland

For inquiries regarding this Special Section, please contact: Bora M. Onat, Managing Editor, IEEE Access (Phone: (732) 562-6036, [email protected] )

At a Glance

• Journal: IEEE Access
• Format: Open Access
• Frequency: Continuous
• Submission to Publication: 4-6 weeks (typical)
• Topics: All topics in IEEE
• Average Acceptance Rate: 27%
• Impact Factor: 3.4
• Model: Binary Peer Review
• Article Processing Charge: US $1,995

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Electrostatic Motors Reach the Macro Scale

It turns out that benjamin franklin was on to something in 1747.

It’s a pretty sure bet that you couldn’t get through a typical day without the direct support of dozens of electric motors. They’re in all of your appliances not powered by a hand crank, in the climate-control systems that keep you comfortable, and in the pumps, fans, and window controls of your car. And although there are many different kinds of electric motors, every single one of them, from the 200-kilowatt traction motor in your electric vehicle to the stepper motor in your quartz wristwatch , exploits the exact same physical phenomenon: electromagnetism.

For decades, however, engineers have been tantalized by the virtues of motors based on an entirely different principle: electrostatics. In some applications, these motors could offer an overall boost in efficiency ranging from 30 percent to close to 100 percent, according to experiment-based analysis. And, perhaps even better, they would use only cheap, plentiful materials, rather than the rare-earth elements, special steel alloys, and copious quantities of copper found in conventional motors.

“Electrification has its sustainability challenges,” notes Daniel Ludois , a professor of electrical engineering at the University of Wisconsin in Madison. But “an electrostatic motor doesn’t need windings, doesn’t need magnets, and it doesn’t need any of the critical materials that a conventional machine needs.”

Such advantages prompted Ludois to cofound a company, C-Motive Technologies , to build macro-scale electrostatic motors. “We make our machines out of aluminum and plastic or fiberglass,” he says. Their current prototype is capable of delivering torque as high as 18 newton meters and power at 360 watts (0.5 horsepower)—characteristics they claim are “the highest torque and power measurements for any rotating electrostatic machine.”

The results are reported in a paper, “Synchronous Electrostatic Machines for Direct Drive Industrial Applications,” to be presented at the 2024 IEEE Energy Conversion Congress and Exposition , which will be held from 20 to 24 October in Phoenix, Ariz. In the paper, Ludois and four colleagues describe an electrostatic machine they built, which they describe as the first such machine capable of “driving a load performing industrial work, in this case, a constant-pressure pump system.”

Making Electrostatic Motors Bigger

The machine, which is hundreds of times more powerful than any previous electrostatic motor, is “competitive with or superior to air-cooled magnetic machinery at the fractional [horsepower] scale,” the authors add. The global market for fractional horsepower motors is more than US $8.7 billion , according to consultancy Business Research Insights.

Achieving macro scale wasn’t easy. Electrostatic motors have been available for years, but today, these are tiny units with power output measured in milliwatts. “ Electrostatic motors are amazing once you get below about the millimeter scale, and they get better and better as they get smaller and smaller,” says Philip Krein, a professor of electrical engineering at the University of Illinois Urbana-Champaign. “There’s a crossover at which they are better than magnetic motors.” (Krein does not have any financial connection to C-Motive.)

For larger motors, however, the opposite is true. “At macro scale, electromagnetism wins, is the textbook answer,” notes Ludois. “Well, we’ve decided to challenge that wisdom.”

For this quest he and his team found inspiration in a lesser-known accomplishment of one of the United States’ founding fathers. “The fact is that Benjamin Franklin built and demonstrated a macroscopic electrostatic motor in 1747,” says Krein. “He actually used the motor as a rotisserie to grill a turkey on a riverbank in Philadelphia” (a fact unearthed by the late historian I. Bernard Cohen for his 1990 book Benjamin Franklin’s Science ).

Krein explains that the fundamental challenge in attempting to scale electrostatic motors to the macro world is energy density. “The energy density you can get in air at a reasonable scale with an electric-field system is much, much lower—many orders of magnitude lower—than the density you can get with an electromagnetic system.” Here the phrase “in air” refers to the volume within the motor, called the “air gap,” where the machine’s fields (magnetic for the conventional motor, electric for the electrostatic one) are deployed. It straddles the machine’s key components: the rotor and the stator.

Let’s unpack that. A conventional electric motor works because a rotating magnetic field, set up in a fixed structure called a stator, engages with the magnetic field of another structure called a rotor, causing that rotor to spin. The force involved is called the Lorentz force. But what makes an electrostatic machine go ‘round is an entirely different force, called the Coulomb force. This is the attractive or repulsive physical force between opposite or like electrical charges.

Overcoming the Air Gap Problem

C-Motive’s motor uses nonconductive rotor and stator disks on which have been deposited many thin, closely spaced conductors radiating outward from the disk’s center, like spokes in a bicycle wheel. Precisely timed electrostatic charges applied to these “spokes” create two waves of voltage, one in the stator and another in the rotor. The phase difference between the rotor and stator waves is timed and controlled to maximize the torque in the rotor caused by this sequence of attraction and repulsion among the spokes. To further wring as much torque as possible, the machine has half a dozen each of rotors and stators, alternating and stacked like compact discs on a spindle.

The machine would be feeble if the dielectric between the charges was air. As a dielectric, air has low permittivity, meaning that an electric field in air can not store much energy. Air also has a relatively low breakdown field strength, meaning that air can support only a fairly weak electric field before it breaks down and conducts current in a blazing arc. So one of the team’s greatest challenges was producing a dielectric fluid that has a much higher permittivity and breakdown field strength than air, and that was also environmentally friendly and nontoxic. To minimize friction, this fluid also had to have very low viscosity, because the rotors would be spinning in it. A dielectric with high permittivity concentrates the electric field between oppositely charged electrodes, enabling greater energy to be stored in the space between them. After screening hundreds of candidates over several years, the C-Motive team succeeded in producing an organic liquid dielectric with low viscosity and a relative permittivity in the low 20s. For comparison, the relative permittivity of air is 1.

Another challenge was supplying the 2,000 volts their machine needs to operate. High voltages are necessary to create the intense electric fields between the rotors and stators. To precisely control these fields, C-Motive was able to take advantage of the availability of inexpensive and stupendously capable power electronics, according to Ludois. For their most recent motor, they developed a drive system based on readily available 4.5-kilovolt insulated-gate bipolar transistors , but the rate of advancement in power semiconductors means they have many attractive choices here, and will have even more in the near future.

Ludois reports that C-Motive is now testing a 750-watt (1 hp) motor in applications with potential customers. Their next machines will be in the range of 750 to 3,750 watts (1 to 5 hp), he adds. These will be powerful enough for an expanded range of applications in industrial automation, manufacturing, and heating, ventilating, and air conditioning.

It’s been a gratifying ride for Ludois. “For me, a point of creative pride is that my team and I are working on something radically different that, I hope, over the long term, will open up other avenues for other folks to contribute.”

• New Watch Motor Seeks to Outsmart the Smartwatch ›
• The Smallest, Lightest Solar-Powered Drone Takes Flight ›
• How to Print an Electric Motor ›
• C-Motive: Home Page ›

Glenn Zorpette is editorial director for content development at IEEE Spectrum . A Fellow of the IEEE, he holds a bachelor's degree in electrical engineering from Brown University.

Seaport Electrification Could Slash Emissions Worldwide

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Reinforcement Learning Double DQN for Chip-Level Synthesis of Paper-Based Digital Microfluidic Biochips

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Bibliometrics & citations, view options, recommendations, routing-based synthesis of digital microfluidic biochips.

Microfluidic biochips are replacing the conventional biochemical analyzers, and are able to integrate on-chip all the necessary functions for biochemical analysis. The "digital" biochips are manipulating liquids as discrete droplets on a two-dimensional ...

High-level synthesis for micro-electrode-dot-array digital microfluidic biochips

A digital microfluidic biochip (DMFB) is an attractive technology platform for automating laboratory procedures in biochemistry. However, today's DMFBs suffer from several limitations: (i) constraints on droplet size and the inability to vary droplet ...

Microfluidic biochips are replacing the conventional biochemical analyzers, and are able to integrate on-chip all the basic functions for biochemical analysis. The "digital" microfluidic biochips are manipulating liquids not as a continuous flow, but as ...

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2024 IEEE IES Awards Laureates Announced!

The IEEE Industrial Electronics Society has announced the 2024 recipients of the society’s awards! Congratulations to them! IES would also like to express great appreciations to the IES Awards & Honors Committee chaired by IES Past President Terry Martin.

Dr.-Ing. Eugene Mittelmann Achievement Award

Recipient: qing-long han.

Swinburne University of Technology, Melbourne, Australia

Citation: For outstanding and innovative technologies contributions to networked control systems and multi-agent systems and applications to smart grids

Qing-Long Han received his Ph.D. degree in Control Engineering from East China University of Science and Technology, Shanghai, China, in 1997. He is currently Pro Vice-Chancellor (Research Quality) and a Distinguished Professor at Swinburne University of Technology, Melbourne, Australia. He held various academic and management positions at Griffith University and Central Queensland University, Australia. His research interests include networked control systems, multi-agent systems, time-delay systems, smart grids, unmanned surface vehicles, and neural networks. Professor Han was awarded the 2021 Norbert Wiener Award (the Highest Award in Systems Science and Engineering, and Cybernetics), and the 2021 M. A. Sargent Medal (the Highest Award of the Electrical College Board of Engineers Australia). He was the recipient of the IEEE Systems, Man, and Cybernetics Society Andrew P. Sage Best Transactions Paper Award in 2022, 2020, and 2019, respectively, The IEEE/CAA Journal of Automatica Sinica Norbert Wiener Review Award in 2020, and the IEEE Transactions on Industrial Informatics Outstanding Paper Award in 2020. Professor Han is a Foreign Member of the Academia Europaea (The Academy of Europe). He is a Fellow of the Institute of Electrical and Electronic Engineers (FIEEE), a Fellow of the International Federation of Automatic Control (FIFAC), an Honorary Fellow of the Institution of Engineers Australia (HonFIEAust), and a Fellow of the Chinese Association of Automation (FCAA). He is a Highly Cited Researcher in both Engineering and Computer Science (Clarivate). He was one of Australia’s Top 5 Lifetime Achievers (Research Superstars) in the discipline area of Engineering and Computer Science Engineering and Computer Science (The Australian’s Research Magazine, 2019-2020). He has served as an AdCom Member of IEEE Industrial Electronics Society (IES), a Member of IEEE IES Fellows Committee, a Member of IEEE IES Publications Committee, Chair of IEEE IES Technical Committee on Network-Based Control Systems and Applications, and the Co-Editor-in-Chief of IEEE Transactions on Industrial Informatics. He is currently the Editor-in-Chief of IEEE/CAA Journal of Automatica Sinica and the Co-Editor of Australian Journal of Electrical and Electronic Engineering.

IEEE Bimal Bose Award for Industrial Electronics Applications in Energy Systems

Recipient: maryam saeedifard.

Georgia Institute of Technology, Atlanta, USA

Citation: For contributions to medium- and high-power electronics

Maryam Saeedifard received the Ph.D. degree in electrical engineering from the University of Toronto, in 2008. Since January 2014, she has been with the School of Electrical and Computer Engineering (ECE) at Georgia Institute of Technology, where she is currently a professor and holds a Ken Byers professorship position. Prior to joining Georgia Tech, she was an assistant professor at Purdue University. She is the recipient of Roger Webb’s Excellence in Mentorship Award from the School of Electrical and Computer Engineering at Georgia Tech in 2023, the 8th Nagamori Awards from Nagamori Foundation in 2022, Roger Webb’s Outstanding Mid-Career Faculty Award from the School of Electrical and Computer Engineering at Georgia Tech in 2021, U.S. Clean Energy Education and Empowerment (C3E) Technology Research & Innovation Award from the Department of Energy in 2021, First Place Prize Paper Award from the IEEE Transactions on Power Electronics in 2023, 2022 and 2021, Best Transactions Paper Award of the IEEE Transactions on Industrial Electronics in 2018 and 2016, IEEE J. David Irwin Early Career Award in 2018, U.S. National Academy of Engineering, Frontiers in Engineering in Education in 2012, U.S. National Academy of Engineering, Frontiers in Engineering in 2011, and IEEE Richard M. Bass Outstanding Young Power Electronic Engineer Award in 2010. She is an IEEE Fellow and is currently serving as a Co-Editor-in-Chief of IEEE Trans. on Power Electronics and the director of faculty evaluation and recognition in the School of ECE at Georgia Tech. Her research interests include power electronics and its applications in terrestrial and mobile power systems.

Rudolf Chope Research & Development Award

Recipient: oscar lucia.

University of Zaragoza, Spain – Young Academy of Spain, Spain

Citation: For contributions to power conversion for induction heating

Óscar Lucía (Senior Member, IEEE) received the M.Sc. and Ph.D. degrees (both with honors) in Electrical Engineering from the University of Zaragoza, Spain, in 2006 and 2010, respectively. During 2006 and 2007 he held a research internship at the Bosch and Siemens Home Appliances Group. Since 2008, he has been with the Department of Electronic Engineering and Communications at the University of Zaragoza, Spain, where he is currently a Full Professor. He was a visiting scholar in the Center for Power Electronics Systems (CPES, Virginia Tech. USA) in 2009 and 2012, and the TU Berlin (Germany) in 2019. His main research interests include resonant power conversion, wide-bandgap devices, and digital control, mainly applied to wireless power transfer, induction heating, electric vehicles, and biomedical applications. In these topics, he has published more than 100 international journal papers and 200 conference papers, and he is a co-inventor in more than 60 patent families with over 150 international extensions. Dr. Lucía is a Senior Member of the IEEE and a member of the Aragon Institute for Engineering Research (I3A). He is a Fellow and President of the Young Academy of Spain. Dr. Lucia is an Associate Editor of the IEEE Transactions on Power Electronics, the IEEE Industrial Electronics Magazine (Society News Editor), and the IEEE Open Journal of the Industrial Electronics Society. He has received the “2021 Agustín de Betancourt y Molina Award” by the Spanish Royal Academy of Engineering, the “2020 IEEE Industrial Electronics Magazine Best Paper Award”, the 2023 IEEE CPE/Powereng “Best Paper Award”, the 2009 and 2018 “BSH Industrial Innovation Award”, and the “2021 SAMCA Chair Multidisciplinary Award”, among others. Dr. Lucía is the recipient of the “Leonardo” Scholarship by BBVA foundation.

IEEE J. David Irwin Early Career Award

Recipient: mohammad shadmand.

University of Illinois Chicago, USA

Citation: For outstanding contributions to the resiliency and cybersecurity of power electronics dominated grids

Mohammad B. Shadmand earned his Ph.D. in Electrical Engineering from Texas A&M University, USA, in 2015. He then served as a postdoctoral research associate at Texas A&M from 2015 to 2016, and as a research engineer from 2016 to 2017. From 2017 to 2020, he was an Assistant Professor in the Department of Electrical and Computer Engineering at Kansas State University, USA. From 2020 to 2024, Dr. Shadmand was an Assistant Professor in the Department of Electrical and Computer Engineering at the University of Illinois Chicago, where he also served as the Director of the Intelligent Power Electronics at Grid Edge (IPEG) Research Laboratory. Since 2024, Dr. Shadmand has been an Associate Professor at the University of Illinois Chicago. His current research interests include resilient control of power electronics dominated grids, resilient self-driving grid, collaborative control architecture for network of grid-following and grid-forming inverters, applications of machine learning techniques for inverters dominated power systems, situational awareness and intrusion detection systems for power electronics and smart grid. He has published more than 160 journal and conference papers, 3 book chapters, and has secured more than 15 research grants and industrial projects from esteemed sources such as the U.S. Department of Energy, U.S. National Science Foundation, and Qatar National Research Fund. Dr. Shadmand has also delivered over 15 invited seminars, talks, and lectures at various universities and conferences on these research topics. He is the General Co-Chair of the 50th Annual Conference of the IEEE Industrial Electronics Society (IEEE IECON 2024), Chicago, USA. He is the Technical Program Co-Chair of 19th IEEE CPE-POWERENG 2025, Antalya, Turkey. He served as Technical Program Chair of IEEE International Conference on Smart Grid & Renewable Energy (IEEE SGRE), Qatar in 2019, 2022, and 2024. In 2022, he has served as Guest Editor for special section on artificial intelligence & machine learning applications in smart inverters of IEEE Journal of Emerging and Selected Topics in Industrial Electronics. In 2018, he has served as Guest Editor for special issue on Challenges in Future Grid-Interactive Power Converters: Control Strategies, Optimal Operation, and Corrective Actions in IET Renewable Power Generation. He has served as Associate Editor of IEEE TRANSACTIONS on INDUSTRY APPLICATION. Currently, he is an Associate Editor for the IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS and IET Renewable Power Generation.

Large Language Models (LLMs) for NextG Wireless Networks

Special Presentation by Dr. Hao Zhou and Chengming Hu (McGill U., Canada)

Hosted by the Future Networks Artificial Intelligence & Machine Learning (AIML) Working Group

Date/Time : Thursday, September 5 th , 2024 @ 6 PM EDT

Large Language Models (LLMs) for NextG Wireless Networks:

Fundamentals and Case Studies in Network Optimization and Prediction

Large language models (LLMs) have received considerable attention recently due to their outstanding comprehension and reasoning capabilities, leading to great progress in many fields. The advancement of LLM techniques also offers promising opportunities to automate many tasks in the communication networks field. After pre-training and fine-tuning, LLMs can perform diverse downstream tasks based on human instructions, paving the way to artificial general intelligence (AGI)-enabled 6G. This talk will first present a comprehensive overview of LLM fundamentals and applications to wireless networks, discussing wireless-specific LLM training, fine-tuning, and practical deployment. Then, it will present two case studies on specific network optimization and prediction problems, showing detailed prompt and algorithm designs along with simulation results.

Dr. Hao Zhou is currently a Postdoctoral Researcher at the School of Computer Science, McGill University. He completed my PhD degree at University of Ottawa, Canada, from 2019 to 2023. His research focuses on the intersection between machine learning, optimization, and networked systems, especially for 5G/6G wireless networks and power systems. Dr. Zhou is dedicated to developing novel machine learning algorithms to address a series of optimization problems in networked systems, including resource allocation, computational task offloading, energy efficiency enhancement, energy management and trading, network security, etc. He has published more than 30 peer-reviewed papers, including reputable journals in IEEE Communication and Power Energy Societies, e.g., IEEE Wireless Communications, IEEE Trans. Smart Grid, and IEEE Communications Survey & Tutorials. He has received the Best Paper Award at the 2023 IEEE ICC conference, and the 2023 IEEE ComSoc CSIM TC Best Journal Paper Award for his contributions to transfer learning-enabled wireless network slicing. Dr. Zhou’s PhD Thesis entitled “ML-Based Optimization of Large-Scale Systems: Case Study in Smart Microgrids and 5G RAN” won the 2023 Faculty of Engineering’s Best Doctoral Thesis Award at University of Ottawa.

Chengming Hu is currently a Ph.D. candidate at McGill University, Canada. He received M.Sc. in Quality Systems Engineering with Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Canada, in 2019. His research interests focus on investigating computational intelligence techniques to enhance the effectiveness and security of IoT systems, including ensemble learning, knowledge distillation, language model, and feature learning, etc. He is actively working on various real-world applications, including power systems, communication systems, and transportation systems. His work has been published in top-tier, peer-reviewed conferences and journals, including ICLR, IEEE TSG, and IEEE PESGM, etc.

  Date and Time

  location,   hosts,   registration.

• Date: 05 Sep 2024
• Time: 06:00 PM to 07:00 PM
• All times are (UTC-04:00) Eastern Time (US & Canada)

• Contact Event Hosts

Baw Chng <[email protected]>

• Co-sponsored by Artificial Intelligence & Machine Learning (AIML) Working Group
• Starts 20 August 2024 05:00 PM
• Ends 05 September 2024 07:00 PM
• No Admission Charge

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