From the 1 of 6 linked papers with an AI index.
6 papers
Where to Touch, How to Contact: A Hierarchical RL-MPC Framework for Geometry-Aware Sim-to-Real Manipulation
Zhixian Xie, Yu Xiang, Michael Posa +1
The paper introduces a hierarchical framework that uses a high‑level reinforcement learning policy to choose where a robot should touch an object and a low‑level contact‑implicit m…
Cross-Embodiment Robot Manipulation via a Unified Hand Action Space
Luis Felipe Casas, Robert Teal, Keval Shah +3
Robot manipulation policies are typically tied to specific robotic hand embodiments, limiting the transfer of learned behaviors across platforms with different kinematic structures…
TwinTrack: Bridging Vision and Contact Physics for Real-Time Tracking of Unknown Objects in Contact-Rich Scenes
Wen Yang, Zhixian Xie, Yiting Wang +4
Real-time tracking of previously unseen, highly dynamic objects in contact-rich scenes, such as during dexterous in-hand manipulation, remains a major challenge. Pure vision-based…
ContactGaussian-WM: Learning Physics-Grounded World Model from Videos
Meizhong Wang, Wanxin Jin, Kun Cao +2
Developing world models that understand complex physical interactions is essential for advancing robotic planning and simulation.However, existing methods often struggle to accurat…
Shape control of simulated multi-segment continuum robots via Koopman operators with per-segment projection
Eron Ristich, Jiahe Wang, Lei Zhang +4
Soft continuum robots can allow for biocompatible yet compliant motions, such as the ability of octopus arms to swim, crawl, and manipulate objects. However, current state-of-the-a…
ContactSDF: Signed Distance Functions as Multi-Contact Models for Dexterous Manipulation
Wen Yang, Wanxin Jin
In this paper, we propose ContactSDF, a method that uses signed distance functions (SDFs) to approximate multi-contact models, including both collision detection and time-stepping…