2 citations · 9 across the 32 of their papers we have counts for
6 papers · 1 filter
The contraction of solutions with large perturbation in multiple space dimensions from the oscillatory dispersive planar shock
Geng Chen, Harish Ravichandar, Yannan Shen
In this paper, we show the contraction property of the planar oscillatory or monotone dispersive shock profiles of the dissipative Kadomtsev-Petviashvili (KP) equation modell…
OmniTacTune: Policy-Agnostic Real-World RL for Tactile Residual Adaptation of Visual Policies
Kelin Yu, Haode Zhang, Harish Ravichandar +2
Visual policies learned from human videos, teleoperation, and robot demonstrations offer scalable motion priors, but often fail in contact-rich manipulation, where success signific…
Video2Sim2Real: Full-Stack Autonomous Dexterous Skill Acquisition from a Single Human Video
Yunhai Han, Jianuo Qiu, Linhao Bai +14
Human manipulation videos are a convenient and intuitive source for robot learning. However, directly transferring human dexterity to robots remains challenging due to perception e…
Distributionally Robust Control via Stein Variational Inference for Contact-Rich Manipulation
Hrishikesh Sathyanarayan, Victor Vantilborgh, Harish Ravichandar +2
Reliable robotic manipulation requires control policies that can accurately represent and adapt to uncertainty arising from contact-rich interactions. Modern data-driven methods mi…
Modeling and Optimizing the Provisioning of Exhaustible Capabilities for Simultaneous Task Allocation and Scheduling
Jinwoo Park, Harish Ravichandar, Seth Hutchinson
Deploying heterogeneous robot teams to accomplish multiple tasks over extended time horizons presents significant computational challenges for task allocation and planning. In this…
Learning and Optimizing the Efficacy of Spatio-Temporal Task Allocation under Temporal and Resource Constraints
Jiazhen Liu, Glen Neville, Jinwoo Park +2
Complex multi-robot missions often require heterogeneous teams to jointly optimize task allocation, scheduling, and path planning to improve team performance under strict constrain…