Papers
19
Total Citations
1,024
H-Index
13
About
Jeremy Ma is a robotics researcher whose work spans mobile robot navigation, legged locomotion, and dexterous manipulation. He is perhaps best known for his foundational contributions to robot navigation in dense human crowds, where his highly cited studies (271 and 163 citations) tackled the "freezing robot problem" and pioneered probabilistic frameworks that encourage cooperative human-robot interaction — work that remains central to modern social robotics. Ma has also made significant contributions to legged robotics through his involvement with RoboSimian, JPL's quadrupedal robot, co-authoring key papers on its hardware design and semi-autonomous manipulation capabilities (130 and 86 citations). His team's 5th-place finish at the 2015 DARPA Robotics Challenge Finals stands as a notable real-world achievement. Complementing these efforts, Ma has advanced robust multi-sensor pose estimation for legged robots operating in GPS-denied, day/night environments, and developed sophisticated techniques in dexterous manipulation, including tactile-based object localization, sensor-guided arm tracking, and probabilistic object search. Across his body of work, Ma bridges perception, planning, and physical interaction, making meaningful contributions to robots that must operate reliably and collaboratively in complex, unstructured environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2Robot navigation in dense human crowds: the case for cooperation163 citations · 2013
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- 7End-to-end dexterous manipulation with deliberate interactive estimation45 citations · 2012
- 8The next best touch for model-based localization43 citations · 2013
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- 10A probabilistic framework for object search with 6-DOF pose estimation31 citations · 2011