2 citations · 2 across the 6 of their papers we have counts for
6 papers · 1 filter
OIL: An Object Interaction Layer for Humanoid Whole-Body Control
Pranay Dugar, Mohitvishnu S. Gadde, Rajesh Mangannavar +2
Recent progress in learned whole-body controllers for humanoid robots has enabled robust free-space motion by tracking kinematic targets such as joint or end-effector trajectories.…
Collision-Aware Humanoid Whole-Body Control under Imperfect Tracking Targets
Mohitvishnu S. Gadde, Ashish Malik, Pranay Dugar +3
Humanoid robots often execute motion commands through whole-body controllers (WBCs) that track targets while maintaining balance and stability. However, most WBCs are blind to scen…
No More Marching: Learning Humanoid Locomotion for Short-Range SE(2) Targets
Pranay Dugar, Mohitvishnu S. Gadde, Jonah Siekmann +3
Humanoids operating in real-world workspaces must frequently execute task-driven, short-range movements to SE(2) target poses. To be practical, these transitions must be fast, robu…
No More Blind Spots: Learning Vision-Based Omnidirectional Bipedal Locomotion for Challenging Terrain
Mohitvishnu S. Gadde, Pranay Dugar, Ashish Malik +1
Effective bipedal locomotion in dynamic environments, such as cluttered indoor spaces or uneven terrain, requires agile and adaptive movement in all directions. This necessitates o…
Learning Multi-Modal Whole-Body Control for Real-World Humanoid Robots
Pranay Dugar, Aayam Shrestha, Fangzhou Yu +2
A major challenge in humanoid robotics is designing a unified interface for commanding diverse whole-body behaviors, from precise footstep sequences to partial-body mimicry and joy…
Revisiting Reward Design and Evaluation for Robust Humanoid Standing and Walking
Bart van Marum, Aayam Shrestha, Helei Duan +3
A necessary capability for humanoid robots is the ability to stand and walk while rejecting natural disturbances. Recent progress has been made using sim-to-real reinforcement lear…