基于测地线追踪的接触建模，让机械手更精准抓握复杂物体。

Reasoning about rolling and sliding contact, or roll-slide contact for short, is critical for dexterous manipulation tasks that involve intricate geometries. But existing works on roll-slide contact mostly focus on continuous shapes with differentiable parametrizations. This work extends roll-slide contact modeling to manifold meshes. Specifically, we present an integration scheme based on geodesic tracing to first-order time-integrate roll-slide contact directly on meshes, enabling dexterous manipulation to reason over high-fidelity discrete representations of an object's true geometry. Using our method, we planned dexterous motions of a multi-finger robotic hand manipulating five objects in-hand in simulation. The planning was achieved with a least-squares optimizer that strives to maintain the most stable instantaneous grasp by minimizing contact sliding and spinning. Then, we evaluated our method against a baseline using collision detection and a baseline using primitive shapes. The results show that our method performed the best in accuracy and precision, even for coarse meshes. We conclude with a future work discussion on incorporating multiple contacts and contact forces to achieve accurate and robust mesh-based surface contact modeling.