5 papers
Fast and Safe Trajectory Optimization for Mobile Manipulators With Neural Configuration Space Distance Field
Yulin Li, Zhiyuan Song, Yiming Li +8
Mobile manipulators promise agile, long-horizon behavior by coordinating base and arm motion, yet whole-body trajectory optimization in cluttered, confined spaces remains difficult…
Geometry-aware Policy Imitation
Yiming Li, Nael Darwiche, Amirreza Razmjoo +4
We propose a Geometry-aware Policy Imitation (GPI) approach that rethinks imitation learning by treating demonstrations as geometric curves rather than collections of state-action…
From Movement Primitives to Distance Fields to Dynamical Systems
Yiming Li, Sylvain Calinon
Developing autonomous robots capable of learning and reproducing complex motions from demonstrations remains a fundamental challenge in robotics. On the one hand, movement primitiv…
Safe Dynamic Motion Generation in Configuration Space Using Differentiable Distance Fields
Xuemin Chi, Yiming Li, Jihao Huang +3
Generating collision-free motions in dynamic environments is a challenging problem for high-dimensional robotics, particularly under real-time constraints. Control Barrier Function…
A Riemannian Take on Distance Fields and Geodesic Flows in Robotics
Yiming Li, Jiacheng Qiu, Sylvain Calinon
Distance functions are crucial in robotics for representing spatial relationships between a robot and its environment. They provide an implicit, continuous, and differentiable repr…