TACTFUL: Tactile-Driven Exploration For Object Localization and Identification in Confined Environments
arXiv:2606.24712v1 Announce Type: cross Abstract: Humans effortlessly locate and identify objects by touch alone, even without vision. In contrast, robotic systems rely heavily on vision and struggle with autonomous tactile exploration and object identification. We present TACTFUL, a vision-free tactile exploration framework that enables a multi-fingered robot to autonomously explore confined workspaces, discover objects through contact, and identify them via tactile reconstruction. Trained entirely on real hardware without simulation, our system learns a single policy that balances global wor
The announcement of TACTFUL, trained entirely on real hardware for autonomous tactile exploration, signals a significant step in robotics advancing beyond vision-centric dependecies.
This development moves robotics closer to operating effectively in complex, unstructured, and confined environments, expanding their operational capabilities significantly beyond current limitations.
Robots can now identify objects and navigate solely by touch, enabling tasks in low-visibility or inaccessible areas where traditional vision-based systems fail.
- · Robotics industry
- · Logistics & manufacturing
- · Exploration (space, deep sea)
- · Companies reliant solely on vision-based robotic solutions
Increased robot autonomy and capability in dark, dusty, or spatially constrained environments.
Development of new robotic applications in disaster recovery, precision assembly, and subterranean exploration.
Reduced need for highly structured environments in automation, leading to wider robotic deployment in varied settings.
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Read at arXiv cs.AI