Intelligent Human–Robot Interaction Systems Using Reinforcement Learning and Neural Networks

DOI10.1007/978-3-319-40533-9_8zbMath1418.93180OpenAlexW2584486528MaRDI QIDQ5223140

Frank L. Lewis, Hamidreza Modares, Bakur Alqaudi, Isura Ranatunga, Dan O. Popa

Publication date: 17 July 2019

Published in: Trends in Control and Decision-Making for Human–Robot Collaboration Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-40533-9_8

zbMATH Keywords

reinforcement learningadaptive impedance controlhuman-robot interactionneuro-adaptive control

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Feedback control (93B52) Applications of optimal control and differential games (49N90) Nonlinear systems in control theory (93C10) Adaptive control/observation systems (93C40) Automated systems (robots, etc.) in control theory (93C85) Control/observation systems governed by ordinary differential equations (93C15) Artificial intelligence for robotics (68T40)

Cites Work

• Neural network approach to continuous-time direct adaptive optimal control for partially unknown nonlinear systems
• Adaptive impedance control to enhance human skill on a haptic interface system
• Adaptive optimal control for continuous-time linear systems based on policy iteration
• Impedance Control: An Approach to Manipulation: Part I—Theory
• Approximate Dynamic Programming
• Reinforcement Learning and Feedback Control: Using Natural Decision Methods to Design Optimal Adaptive Controllers
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