Safe Self-Supervised Learning in Real of Visuo-Tactile Feedback Policies for Industrial Insertion
Author:
Affiliation:
1. The AUTOLab at UC Berkeley
2. Karlsruhe Institute of Technology
3. Autodesk Research
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10160211/10160212/10160763.pdf?arnumber=10160763
Reference36 articles.
1. GelSight: High-Resolution Robot Tactile Sensors for Estimating Geometry and Force
2. You only demonstrate once: Category-level manipulation from single visual demonstration;wen;Robotics Science and Systems (RSS),2022
3. DIGIT: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor With Application to In-Hand Manipulation
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2. An Electromagnetism-Inspired Method for Estimating In-Grasp Torque from Visuotactile Sensors;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13
3. Bridging the Sim-to-Real Gap with Dynamic Compliance Tuning for Industrial Insertion;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13
4. When Vision Meets Touch: A Contemporary Review for Visuotactile Sensors From the Signal Processing Perspective;IEEE Journal of Selected Topics in Signal Processing;2024-04
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