TouchWorld: Giving Robots a Sense of Touch
量子位 · wechat · 2026-07-12
This article introduces the tactile approach of Yang Shuo's team at Harbin Institute of Technology (Shenzhen) and their startup PHANESAI: from collecting visual-tactile data via EgoTouch, to recovering touch from first-person videos using TouchAnything, to integrating tactile feedback into world models and manipulation policies with TouchWorld.
What TouchWorld Does
- Predicts not only visual changes but also how contact occurs and what the target contact state should be.
- Introduces high-frequency tactile feedback during execution for real-time action correction, making it particularly effective for contact-intensive tasks like grasping, plugging, pressing, and wiping.
Experimental Results
- Tested on 6 real-world robot tasks, including watering plants, clearing tables, plugging in power cords, inserting cups, wiping pots, and pulling tissues.
- Achieved an average success rate of 65.0% in clean settings and 57.2% under human disturbance scenarios.
- Outperformed baseline methods by 15.7 and 16.0 percentage points in the two settings, respectively.
Core Insights
- Tactile sensing is not just "another sensor"; it is a critical infrastructure for embodied AI to enter the real world.
- Vision and language alone are insufficient; robots need to know if they have made contact, grasped firmly, slipped, or applied appropriate force, and how to quickly correct themselves during contact.
- The team is also advancing data collection, evaluation, and control loops for whole-body mobile dexterous manipulation in humanoid robots.
Related event: TouchWorld: A Tactile World Model for Robot Error Correction(2 posts)→
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