Papers
5
Total Citations
38
H-Index
4
About
Arjun Lakshmipathy is a robotics researcher whose work sits at the intersection of soft robotics, dexterous manipulation, and human-robot transfer. His primary contributions focus on making robotic hands more accessible, printable, and controllable. In his highly cited 2022 work, *Towards Very Low-Cost Iterative Prototyping for Fully Printable Dexterous Soft Robotic Hands* (15 citations), he pioneered a rapid fabrication pipeline that dramatically reduces the cost and complexity of building soft, dexterous hands. He further advanced the field by developing novel methods for transferring human grasps to robots, notably through *Contact Transfer* (8 citations), which preserves contact shapes without requiring model training or grasp sampling. His *Kinematic Motion Retargeting* (2025, 9 citations) addresses the challenge of mapping human motion capture data onto robots with different geometries and degrees of freedom. Lakshmipathy also contributed to contact reconstruction with *Contact Tracing* (4 citations), a low-cost framework for tracking surface contact during in-hand manipulations. Earlier, his work on *Deep Learning of Neuromuscular and Visuomotor Control of a Biomimetic Simulated Humanoid* (2 citations) explored biologically inspired control for humanoid robots. Collectively, his research is shaping the future of affordable, dexterous, and human-like robotic hands.
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