Geodesic Tracing-Based Kinematic Integration of Rolling and Sliding Contact on Manifold Meshes for Dexterous In-Hand Manipulation
Sunyu Wang, Arjun S. Lakshmipathy, Jean Oh, and Nancy S. Pollard

TL;DR
This paper introduces a geodesic tracing-based integration scheme for modeling roll-slide contact directly on manifold meshes, improving dexterous in-hand manipulation planning accuracy over existing methods.
Contribution
It extends roll-slide contact modeling to manifold meshes and enables high-fidelity, mesh-based contact reasoning for dexterous manipulation planning.
Findings
Our method outperforms collision detection baselines in accuracy and precision.
It successfully plans dexterous motions with multi-finger robotic hands on complex objects.
The approach maintains stable grasping by minimizing contact sliding and spinning.
Abstract
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…
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Taxonomy
TopicsRobot Manipulation and Learning · Hand Gesture Recognition Systems · Teleoperation and Haptic Systems
