TAPNAV: Humanoid Navigation through Tactile Active Perception

What happened

arXiv:2610.10748v1 Announce Type: new Abstract: Navigation in vision-denied environments is challenging for humanoid robots because proprioceptive odometry drifts and localization uncertainty accumulates rapidly. The global planner searches for routes that keep predicted localization uncertainty bounded by exploiting opportunities for tactile correction, while the local planner selects probe actions that maximize expected information gain.

TAPNAV maintains a pose belief from odometry, IMU, and tactile contact observations, and couples uncertainty-aware global route planning with information-gain-driven local probing. A whole-body controller coordinates the humanoid's locomotion and end-effector contact to execute the planned navigation and probe motions. TAPNAV achieves lower state estimation error and a higher task completion rate than baselines.