基于测地线追踪的流形网格上滚动与滑动接触的运动学积分方法用于灵巧手中操作
Geodesic Tracing-Based Kinematic Integration of Rolling and Sliding Contact on Manifold Meshes for Dexterous In-Hand Manipulation
AI总结：
本文提出基于测地线追踪的积分方案，将滚滑接触建模扩展到流形网格，实现高保真离散几何上的灵巧手中操作规划，并通过仿真验证其在准确性和精度上优于碰撞检测和原始形状基线。
摘要：
对滚动与滑动接触（简称滚滑接触）进行推理，对于涉及复杂几何形状的灵巧操作任务至关重要。但现有关于滚滑接触的研究大多集中于具有可微参数化的连续形状。本工作将滚滑接触建模扩展到流形网格。具体而言，我们提出一种基于测地线追踪的积分方案，直接在网格上对滚滑接触进行一阶时间积分，从而使灵巧操作能够基于物体真实几何的高保真离散表示进行推理。利用我们的方法，我们在仿真中规划了一只多指机械手对五个物体进行手中操作的灵巧运动。该规划通过一个最小二乘优化器实现，该优化器通过最小化接触滑动和旋转来努力维持最稳定的瞬时抓取。随后，我们将我们的方法与使用碰撞检测的基线和使用原始形状的基线进行了评估对比。结果表明，即使在粗糙网格上，我们的方法在准确性和精度方面也表现最佳。最后，我们讨论了未来工作，即引入多重接触和接触力以实现准确且鲁棒的基于网格的表面接触建模。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
