3 citations · 3 across the 6 of their papers we have counts for
5 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.…
Learning Multi-Humanoid Pickup and Transport via Decentralized Object-Centric Control
Bikram Pandit, Mohitvishnu S. Gadde, Aayam Kumar Shrestha +1
We study cooperative multi-humanoid pickup and transport of objects with varying size, weight, and geometry, requiring robot teams of different sizes. Our approach uses decentraliz…
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…
Grounding Vision and Language to 3D Masks for Long-Horizon Box Rearrangement
Ashish Malik, Caleb Lowe, Aayam Shrestha +3
We study long-horizon planning in 3D environments from under-specified natural-language goals using only visual observations, focusing on multi-step 3D box rearrangement tasks. Exi…
Humanoid Hanoi: Investigating Shared Whole-Body Control for Skill-Based Box Rearrangement
Minku Kim, Kuan-Chia Chen, Aayam Shrestha +3
We introduce \emph{Humanoid Hanoi}, a challenge problem for long-horizon humanoid skill composition that requires a robot to repeatedly sequence pickup, locomotion, and placement s…