TAPNAV: Humanoid Navigation through Tactile Active Perception
We present TAPNAV, a tactile active-perception framework that enables humanoid navigation toward a goal by actively probing surrounding structures without relying on vision.
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Key points
- Navigation in vision-denied environments is challenging for humanoid robots because proprioceptive odometry drifts and localization uncertainty accumulates rapidly.
- 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.
- 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.
- These results demonstrate that actively planning physical interactions with the environment can provide localization cues for reliable humanoid navigation without vision.
Sources (1)
- [1]TAPNAV: Humanoid Navigation through Tactile Active PerceptionarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 7, 06:14 PM
We present TAPNAV, a tactile active-perception framework that enables humanoid navigation toward a goal by actively probing surrounding structures without relying on vision.
Navigation in vision-denied environments is challenging for humanoid robots because proprioceptive odometry drifts and localization uncertainty accumulates rapidly.
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