TacDexGrasp: Compliant and Robust Dexterous Grasping with Tactile Feedback

TL;DR

This work addresses two key problems: distributing forces across multiple contacts to counteract an object's weight, and preventing rotational slip caused by gravitational torque when a grasp is distant from the object's center of mass via tactile feedback and a Second-Order Cone Programming (SOCP)-based controller.

Abstract

Multi-fingered hands offer great potential for compliant and robust grasping of unknown objects, yet their high-dimensional force control presents a significant challenge. This work addresses two key problems: (1) distributing forces across multiple contacts to counteract an object's weight, and (2) preventing rotational slip caused by gravitational torque when a grasp is distant from the object's center of mass. We address these challenges via tactile feedback and a Second-Order Cone Programming (SOCP)-based controller, without explicit torque modeling or slip detection. Our key insights are (1) rotational slip inevitably induces translational slip at some contact points for a multi-fingered grasp, and (2) the ratio of tangential to normal force at each contact is an effective early stability indicator. By actively constraining this ratio for each finger below the estimated friction coefficient, our controller maintains grasp stability against both translational and rotational slip. Real-world experiments on 12 diverse objects demonstrate the robustness and compliance of our approach.

Figures (7)

• Figure 1: TacDexGrasp. (A-C) Our system enables stable and safe grasping for multi-fingered hands on objects with diverse, unknown mass distributions, friction coefficients, and deformation materials. (D) Our SOCP-based controller can compensate for gravitational torque to prevent the rotational slip without explicit torque modeling.
• Figure 2: Illustration of our geometric insight: rotational slip inevitably induces translational slip. If the object (black) rotates about the $x$-axis to the dashed pose (green), each $O_i$ moves to $O_i^{\text{new}}$, while $O_1$ stays fixed because it is on the $x$-axis.
• Figure 3: Real World Setup. (Left) 12 diverse objects. (Middle) Friction coefficients of each object. Note that both mass and friction coefficients are presented only as statistics and are not used in the experiments. (Right) The robotic platform used in our study.
• Figure 4: Real-World Experiments. For diverse objects with varying masses, deformability, and friction, our system rapidly adapts and achieves stable grasps. The measured contact forces align closely with the SOCP-derived target forces. Legends denote fingertip labels: TH (thumb), LF (little finger), MF (middle finger), and FF (forefinger).
• Figure 5: Mass Adaptation Test. Our system quickly responds to two sudden mass increases by increasing the target normal forces accordingly.