Papers
10
Total Citations
93
H-Index
6
About
Bhavyansh Mishra is a robotics researcher focused on enabling legged robots—particularly humanoids—to perceive, plan, and locomote autonomously over complex, rough terrain. His core contributions lie at the intersection of real-time perception, terrain mapping, and footstep planning. Mishra pioneered methods for rapidly extracting usable planar regions from depth data, achieving the speed and reliability needed for dynamic behaviors like running, push recovery, and backflips (25 citations). His work on GPU-accelerated planar region extraction (13 citations) and efficient terrain maps (5 citations) directly addresses the computational bottleneck of onboard perception. He also developed a two-stage planning framework that combines A* search with traversability models to generate smooth, collision-free paths for bipedal walking over rough terrain (10 citations). More recently, Mishra has extended his research to high-level autonomy, including a multi-sensor perception engine for humanoid decision-making (8 citations) and a behavior architecture for fast door traversals. With over 90 total citations across his publications, Mishra is establishing himself as a rising figure in legged locomotion, bridging the gap between robust perception and agile, real-world humanoid navigation.
Research Focus
Key Achievements
Top Papers
- 1Detecting Usable Planar Regions for Legged Robot Locomotion25 citations · 2020
- 2A Fast, Autonomous, Bipedal Walking Behavior over Rapid Regions15 citations · 2022
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- 4Bipedal Navigation Planning over Rough Terrain using Traversability Models10 citations · 2023
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- 9A behavior architecture for fast humanoid robot door traversals2 citations · 2025
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