Michael Mistry

3.9k total citations
80 papers, 2.6k citations indexed

About

Michael Mistry is a scholar working on Control and Systems Engineering, Biomedical Engineering and Cognitive Neuroscience. According to data from OpenAlex, Michael Mistry has authored 80 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 56 papers in Control and Systems Engineering, 55 papers in Biomedical Engineering and 13 papers in Cognitive Neuroscience. Recurrent topics in Michael Mistry's work include Robot Manipulation and Learning (43 papers), Robotic Locomotion and Control (39 papers) and Prosthetics and Rehabilitation Robotics (27 papers). Michael Mistry is often cited by papers focused on Robot Manipulation and Learning (43 papers), Robotic Locomotion and Control (39 papers) and Prosthetics and Rehabilitation Robotics (27 papers). Michael Mistry collaborates with scholars based in United Kingdom, United States and Japan. Michael Mistry's co-authors include Stefan Schaal, Jonas Buchli, Stefan Schaal, Mrinal Kalakrishnan, Jun Nakanishi, Jan Peters, Peter Pástor, Ludovic Righetti, Rick Cory and Guiyang Xin and has published in prestigious journals such as The Journal of Physiology, Journal of Neurophysiology and The International Journal of Robotics Research.

In The Last Decade

Michael Mistry

77 papers receiving 2.5k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Michael Mistry United Kingdom 26 1.8k 1.6k 459 380 251 80 2.6k
Gen Endo Japan 28 2.3k 1.3× 1.2k 0.7× 810 1.8× 284 0.7× 227 0.9× 219 2.9k
Luis Sentis United States 20 1.8k 1.0× 1.5k 1.0× 441 1.0× 377 1.0× 99 0.4× 102 2.5k
Máximo A. Roa Germany 25 1.8k 1.0× 1.6k 1.0× 448 1.0× 330 0.9× 231 0.9× 123 2.6k
Thomas Wimböck Germany 25 1.8k 1.0× 1.8k 1.1× 671 1.5× 395 1.0× 196 0.8× 45 2.6k
Sang-Ho Hyon Japan 24 1.7k 0.9× 880 0.6× 300 0.7× 156 0.4× 149 0.6× 98 2.1k
Gill A. Pratt United States 21 3.2k 1.7× 1.6k 1.0× 586 1.3× 245 0.6× 202 0.8× 39 3.9k
Raffaella Carloni Netherlands 26 1.6k 0.9× 996 0.6× 522 1.1× 471 1.2× 398 1.6× 120 2.5k
Jaeheung Park South Korea 23 1.1k 0.6× 1.3k 0.8× 492 1.1× 413 1.1× 109 0.4× 160 2.0k
Katsu Yamane United States 30 1.6k 0.9× 1.8k 1.1× 294 0.6× 936 2.5× 133 0.5× 138 2.9k
Chee–Meng Chew Singapore 23 1.4k 0.8× 636 0.4× 319 0.7× 256 0.7× 259 1.0× 135 2.2k

Countries citing papers authored by Michael Mistry

Since Specialization
Citations

This map shows the geographic impact of Michael Mistry's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Mistry with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Mistry more than expected).

Fields of papers citing papers by Michael Mistry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Mistry. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Mistry. The network helps show where Michael Mistry may publish in the future.

Co-authorship network of co-authors of Michael Mistry

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Mistry. A scholar is included among the top collaborators of Michael Mistry based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michael Mistry. Michael Mistry is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ramamoorthy, Subramanian, et al.. (2024). Achieving Dexterous Bidirectional Interaction in Uncertain Conditions for Medical Robotics. IEEE Transactions on Medical Robotics and Bionics. 7(1). 43–50.
2.
Xin, Guiyang & Michael Mistry. (2024). Optimization-based dynamic motion planning and control for quadruped robots. Nonlinear Dynamics. 112(9). 7043–7056. 5 indexed citations
3.
Mistry, Michael, et al.. (2024). Robust and Dexterous Dual-arm Tele-Cooperation using Adaptable Impedance Control. 17337–17343. 1 indexed citations
4.
Mistry, Michael, et al.. (2023). Collaborative Bimanual Manipulation Using Optimal Motion Adaptation and Interaction Control: Retargeting Human Commands to Feasible Robot Control References. IEEE Robotics & Automation Magazine. 31(4). 68–80. 8 indexed citations
5.
Wang, Ke, et al.. (2023). A unified model with inertia shaping for highly dynamic jumps of legged robots. Mechatronics. 95. 103040–103040. 6 indexed citations
6.
Li, Zhibin, et al.. (2022). Robust Impedance Control for Dexterous Interaction Using Fractal Impedance Controller with IK-Optimisation. 2022 International Conference on Robotics and Automation (ICRA). 840–846. 1 indexed citations
7.
Xin, Guiyang, et al.. (2020). An Optimization-Based Locomotion Controller for Quadruped Robots Leveraging Cartesian Impedance Control. Frontiers in Robotics and AI. 7. 48–48. 30 indexed citations
8.
Babič, Jan, et al.. (2019). Effects of the weighting matrix on dynamic manipulability of robots. Autonomous Robots. 43(7). 1867–1879. 16 indexed citations
9.
Pairet, Èric, et al.. (2019). Learning Generalizable Coupling Terms for Obstacle Avoidance via Low-Dimensional Geometric Descriptors. IEEE Robotics and Automation Letters. 4(4). 3979–3986. 22 indexed citations
10.
Angelini, Franco, Guiyang Xin, Wouter Wolfslag, et al.. (2019). Online Optimal Impedance Planning for Legged Robots. Edinburgh Research Explorer (University of Edinburgh). 6028–6035. 21 indexed citations
11.
Ortenzi, Valerio, et al.. (2018). Vision-Based Framework to Estimate Robot Configuration and Kinematic Constraints. IEEE/ASME Transactions on Mechatronics. 23(5). 2402–2412. 20 indexed citations
12.
Xin, Guiyang, et al.. (2018). Modeling and Control of Multi-Arm and Multi-Leg Robots: Compensating for Object Dynamics During Grasping. Edinburgh Research Explorer. 294–301. 23 indexed citations
13.
Lin, Hsiu-Chin, et al.. (2018). A Projected Inverse Dynamics Approach for Multi-Arm Cartesian Impedance Control. Edinburgh Research Explorer. 5421–5428. 35 indexed citations
14.
Romanò, Francesco, Jernej Čamernik, Claudia Latella, et al.. (2017). The CoDyCo Project Achievements and Beyond: Toward Human Aware Whole-Body Controllers for Physical Human Robot Interaction. IEEE Robotics and Automation Letters. 3(1). 516–523. 17 indexed citations
15.
Nordmann, Arne, et al.. (2017). Domain-Specific Language Modularization Scheme Applied to a Multi-Arm Robotics Use-Case. 8(1). 45–64. 11 indexed citations
16.
Ortenzi, Valerio, et al.. (2016). Model estimation and control of compliant contact normal force. University of Birmingham Research Portal (University of Birmingham). 442–447. 9 indexed citations
17.
Ortenzi, Valerio, et al.. (2014). An experimental study of robot control during environmental contacts based on projected operational space dynamics. University of Birmingham Research Portal (University of Birmingham). 20 indexed citations
18.
Mistry, Michael, Jun Nakanishi, Gordon Cheng, & Stefan Schaal. (2008). Inverse kinematics with floating base and constraints for full body humanoid robot control. 22–27. 53 indexed citations
19.
Mistry, Michael, Jun Nakanishi, Gordon Cheng, & Stefan Schaal. (2008). Humanoids 2008 - 8th IEEE-RAS International Conference on Humanoid Robots. 1 indexed citations
20.
Mistry, Michael, Jun Nakanishi, & Stefan Schaal. (2007). Task space control with prioritization for balance and locomotion. 331–338. 19 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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