Sandip Bhattacharya
Papers
10
Total Citations
107
H-Index
5
About
Sandip Bhattacharya’s research lies at the intersection of legged robotics, force sensing, and autonomous locomotion, with a focus on enabling biped and quadruped robots to walk stably and efficiently across diverse, real-world terrains. His most influential work, a 2009 paper on search-based planning for legged robots over rough terrain (53 citations), established a foundational framework for generating complete joint trajectories from start to goal. Since then, Bhattacharya has pioneered the use of force sensors embedded in robot feet for real-time surface recognition, allowing humanoid robots to identify and adapt to surfaces such as foam, carpet, and tabletop. His key contributions include developing machine-learning algorithms—ranging from neural networks to nearest-neighbor search—that classify walking patterns and dynamically adjust walking speed for stable movement under changing conditions. Notably, his 2019 and 2021 papers on surface-property recognition and walking-pattern classification (each with 14 citations) demonstrate practical, cost-efficient sensing solutions. Bhattacharya’s work also addresses energy efficiency, with a 2020 study quantifying how walking speed and surface type affect power consumption. Collectively, his research advances the goal of truly autonomous, terrain-aware robots capable of safe and robust operation in human environments.
Research Focus
Key Achievements
Top Papers
- 1Search-based planning for a legged robot over rough terrain53 citations · 2009
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- 5Machine learning algorithm for autonomous control of walking robot5 citations · 2018
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- 7Force-Sensor-Based Walking-Environment Recognition of Biped Robots2 citations · 2020
- 8Power Consumption Estimation of Biped Robot During Walking2 citations · 2019
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