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TacO: Evaluating Four Types of Tactile Sensors by Manipulation Task
1 reports · 1 sources
Anya Zorin and other authors propose the TacO framework, which systematically evaluates tactile sensors by manipulation policy performance, covering four modalities: vision, acoustic, magnetic, and resistive. The study trains policies separately on three tasks—unknown-mass pick-and-place, object reorientation, and peg insertion—and analyzes the influence of sensor characteristics such as spatial resolution, shear sensing, tactile representation, and material friction on task performance. The results show that the value of tactile information depends on sensor modality, material properties, and the specific manipulation task, and is not universally beneficial. The authors state that the sensors, code, data, and hardware designs will be made publicly available on the project website.
Report timeline
- TacO: A Benchmark Evaluation of Tactile Sensors for Object Manipulation
The authors propose the TacO framework to systematically evaluate tactile sensors based on manipulation policy performance, covering four modalities: visual, acoustic, magnetic, and resistive. They train separate policies for three tasks—pick-and-place with unknown mass, object reorientation, and plug insertion—and analyze how sensor properties such as spatial resolution, shear sensing, tactile representation, and material friction affect task performance. The results show that the value of tactile information depends on the sensor modality, material properties, and specific manipulation task, rather than being universally beneficial; the sensors, code, data, and hardware designs will be made public on the project website.
arXiv cs.RO ·
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