Papers
7
Total Citations
37
H-Index
4
About
Amisha Bhaskar is a robotics researcher whose work sits at the intersection of aerial-ground coordination, assistive manipulation, and adaptive control. Her research primarily focuses on enabling robots to operate autonomously in complex, real-world environments—from planning coverage paths for energy-constrained UAV-UGV teams (14 citations) to developing robotic assisted feeding systems that restore autonomy for individuals with mobility impairments. Her contributions to assistive robotics are particularly notable: she has advanced food acquisition through visual imitation learning and long-horizon action planning, addressing the challenging problem of generalizing across diverse food types and bowl configurations. Bhaskar has also pushed the boundaries of bipedal walking control with adaptive time delay methods that unify controller design across walking phases, and explored novel robot morphologies with the MARVEL wall-climbing bi-copter. Her recent work on "Sketch-to-Skill" introduces an innovative approach to robot learning by bootstrapping policies from human-drawn trajectory sketches, reducing the need for expert demonstrations. With publications spanning IEEE conferences and journals, Bhaskar’s research demonstrates a commitment to making robots more capable, adaptive, and useful in both industrial and human-centered applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2LAVA: Long-horizon Visual Action based Food Acquisition8 citations · 2024
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- 6MARVEL: A High Pitch Agile Bi-copter Wall-Climbing Robot2 citations · 2021
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