TAC-LOCO: Tactile-Informed Whole-Body Control for Quadrupedal Loco-Manipulation

Jul 14, 2026

Researchers have developed TAC-LOCO, a reinforcement learning framework that incorporates tactile sensing from compliant grippers into the unified whole-body control of quadrupedal robots. The system encodes tactile data into a compact representation, enabling the robot to coordinate its legs, arm, and gripper for dynamic loco-manipulation tasks. In zero-shot experiments on a Unitree Go2 robot, TAC-LOCO achieved a 47% reduction in grasping force and maintained an object drop rate of less than 1%.

Why it matters: This work demonstrates that integrating tactile feedback into whole-body control can significantly improve the efficiency and reliability of dynamic manipulation in legged robots.

Full story at: arXiv Robotics ↗