Rigidity-Based Multi-Finger Coordination for Precise In-Hand Manipulation of Force-Sensitive Objects

TL;DR

This paper introduces a rigidity-based multi-finger coordination framework that enables precise in-hand manipulation of force-sensitive objects without tactile feedback, using graph rigidity and force closure constraints for joint control.

Contribution

It presents a novel dual-layer control framework that leverages graph rigidity for high-precision, safe manipulation of fragile objects with dexterous hands lacking tactile sensors.

Findings

Successfully manipulated fragile objects like eggs and yarns with high precision.

Validated the framework on a custom dexterous hand demonstrating safety and accuracy.

Achieved manipulation without tactile feedback using force-to-position mapping.

Abstract

Precise in-hand manipulation of force-sensitive objects typically requires judicious coordinated force planning as well as accurate contact force feedback and control. Unlike multi-arm platforms with gripper end effectors, multi-fingered hands rely solely on fingertip point contacts and are not able to apply pull forces, therefore poses a more challenging problem. Furthermore, calibrated torque sensors are lacking in most commercial dexterous hands, adding to the difficulty. To address these challenges, we propose a dual-layer framework for multi-finger coordination, enabling high-precision manipulation of force-sensitive objects through joint control without tactile feedback. This approach solves coordinated contact force planning by incorporating graph rigidity and force closure constraints. By employing a force-to-position mapping, the planned force trajectory is converted to a joint trajectory. We validate the framework on a custom dexterous hand, demonstrating the capability to manipulate fragile objects-including a soft yarn, a plastic cup, and a raw egg-with high precision and safety.