arXiv:2606.31694v1 Announce Type: cross Abstract: For robots manipulating open-world objects, tactile representations must generalize to unseen materials. We introduce RCT (Robotic Contact Tactile), a robot-collected touch-vision-language dataset with 29,279 tactile frames from full robot presses on 122 industrial reference materials in 7 categories, recorded with three DIGIT sensors at multiple contact positions. RCT preserves each press as a contact sequence, enabling held-out evaluation across materials, categories, sensors, contact positions, and contact sequences. Frames from one press ar
The increasing sophistication of robotics and AI requires more nuanced sensory data, driving the creation of large-scale, multimodal datasets for generalization.
This dataset significantly advances robotic tactile perception, crucial for robots to operate effectively in unstructured, real-world environments and handle diverse objects.
Robots will gain improved capabilities for object manipulation and interaction, moving beyond purely visual perception to incorporate nuanced touch feedback.
- · Robotics companies
- · AI hardware manufacturers (sensors)
- · Manufacturing sector
- · Logistics and e-commerce
- · Tasks requiring highly dextrous human manipulation
Increased research and development in tactile AI and robotic manipulation.
Accelerated deployment of general-purpose robots in industries requiring fine motor skills and material handling.
Enhanced automation leading to new economic models for production and labor.
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