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Chapter and Conference Paper
A Multi-expert Agent for Efficient Learning from Demonstrations
In recent years, a myriad of seminal works on intelligent agents have been proposed, thanks to the advances in machine learning. Nonetheless, limited training efficiency and lack of transfer ability have been ...
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Chapter and Conference Paper
Real2Sim or Sim2Real: Robotics Visual Insertion Using Deep Reinforcement Learning and Real2Sim Policy Adaptation
Reinforcement learning has shown a wide usage in robotics tasks, such as insertion and gras**. However, without a practical sim2real strategy, the policy trained in simulation could fail on the real task. Th...
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Chapter and Conference Paper
Localization on Indoor Topological Maps—SCAM: Scale-Compatible Adaptive Monte-Carlo Localization
This paper introduces Scale Compatible Adaptive Monte-Carlo Localization (SCAM) to localize on topological maps, such as hand-drawn maps and floor plans. This enables fast modifications to maps of indoor space...
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Book and Living Reference Work (Continuously updated edition)
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Chapter and Conference Paper
Adaptive Friction Compensation Using a Velocity Observer
In this paper, adaptive friction compensation and identification issues are investigated. The friction adaptation law is formulated by utilizing both observed and desired velocity information. The overall adap...
