6 papers
A scaling law for large-deformation contact in soft materials
Tong Mu, Shizhuo Weng, Changhong Linghu +10
Compression of soft bodies is central to biology, materials science, and robotics, yet existing contact theories break down at large deformations. Here, we develop a general framew…
Recasting Classical Motion Planning for Contact-Rich Manipulation
Lin Yang, Huu-Thiet Nguyen, Chen Lv +1
In this work, we explore how conventional motion planning algorithms can be reapplied to contact-rich manipulation tasks. Rather than focusing solely on efficiency, we investigate…
A Planning Framework for Stable Robust Multi-Contact Manipulation
Lin Yang, Sri Harsha Turlapati, Zhuoyi Lu +2
While modeling multi-contact manipulation as a quasi-static mechanical process transitioning between different contact equilibria, we propose formulating it as a planning and optim…
Generalizing Robot Trajectories from Single-Context Human Demonstrations: A Probabilistic Approach
Qian Ying Lee, Suhas Raghavendra Kulkarni, Kenzhi Iskandar Wong +4
Generalizing robot trajectories from human demonstrations to new contexts remains a key challenge in Learning from Demonstration (LfD), particularly when only single-context demons…
Path Planning in Complex Environments with Superquadrics and Voronoi-Based Orientation
Lin Yang, Ganesh Iyer, Baichuan Lou +3
Path planning in narrow passages is a challenging problem in various applications. Traditional planning algorithms often face challenges in complex environments like mazes and trap…
Planning for quasi-static manipulation tasks via an intrinsic haptic metric: a book insertion case study
Lin Yang, Sri Harsha Turlapati, Chen Lv +1
Contact-rich manipulation often requires strategic interactions with objects, such as pushing to accomplish specific tasks. We propose a novel scenario where a robot inserts a book…