Application of Reinforcement Learning to UR10 Positioning for Prioritized Multi-Step Inspection in NVIDIA Omniverse
Author:
Affiliation:
1. Dresden University of Applied Sciences,Dresden,Germany
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10210887/10212105/10212317.pdf?arnumber=10212317
Reference16 articles.
1. Abstract Demonstrations and Adaptive Exploration for Efficient and Stable Multi-step Sparse Reward Reinforcement Learning
2. Overcoming Exploration in Reinforcement Learning with Demonstrations
3. Calibration of UR10 Robot Controller through Simple Auto-Tuning Approach
4. Multi-step motion learning by combining learning-from-demonstration and policy-search
5. The Intelligent Path Planning System of Agricultural Robot via Reinforcement Learning
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