Mark Malhotra
Papers
9
Total Citations
190
H-Index
9
About
Mark Malhotra is a leading researcher in the fields of robotic dexterity, neuromuscular control, and prosthetic sensory feedback. His work centers on understanding and replicating the extraordinary capabilities of the human hand, with major contributions in the development of the Anatomically Correct Testbed (ACT) Hand—a robotic platform meticulously designed to capture the biomechanical features of human anatomy. Malhotra has pioneered the application of reinforcement learning and synergy-based control to simplify the high-dimensional, nonlinear control of tendon-driven systems, enabling robots to learn complex, compliant movements. His research on remote vibrotactile and pressure feedback for prosthetic hands has provided critical insights into restoring sensory feedback for amputees. With his most-cited paper, "Musical piano performance by the ACT Hand" (37 citations), he demonstrated the system's ability to produce expressive, human-like music. His work on path integral reinforcement learning (22 citations) has advanced the control of both biomechanical and robotic systems. Through over 190 total citations, Malhotra’s research bridges robotics, neuroscience, and rehabilitation, offering transformative approaches to dexterous manipulation and prosthetic design.
Research Focus
Key Achievements
Top Papers
- 1Musical piano performance by the ACT Hand37 citations · 2011
- 2Reinforcement Learning and Synergistic Control of the ACT Hand33 citations · 2012
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- 6Reduced dimensionality control for the ACT hand14 citations · 2012
- 7Tendon-Driven Variable Impedance Control Using Reinforcement Learning12 citations · 2012
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- 9Tendon-Driven Variable Impedance Control Using Reinforcement Learning10 citations · 2013