AI based Robot Safe Learning and Control

AI based Robot Safe Learning and Control

This open access book mainly focuses on the safe control of robot manipulators. The control schemes are mainly developed based on dynamic neural network, which is an important theoretical branch of deep reinforcement learning. In order to enhance the safety performance of robot systems, the control...

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Detalles Bibliográficos
Autores principales: Zhou, Xuefeng. author (author), Xu, Zhihao. author, Li, Shuai. author, Wu, Hongmin. author, Cheng, Taobo. author, Lv, Xiaojing. author
Formato: Libro electrónico
Idioma:Inglés
Publicado: Singapore Springer Nature 2020
Singapore : 2020.
Edición:1st ed. 2020.
Materias:
Robotics.
Automation.
Control engineering.
Artificial intelligence.
Robotics and Automation.
Control and Systems Theory.
Artificial Intelligence.
Robotics and Automation
Control and Systems Theory
Artificial Intelligence
Robotic Engineering
Safe Control
Deep Reinforcement Learning
Recurrent Neural Network
Force Control
Obstacle Ovoidance
Adaptive Control
Trajectory Tracking
Open Access
Robotics
Automatic control engineering
Artificial intelligence
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009429756406719
Tabla de Contenidos:
  • Adaptive Jacobian based Trajectory Tracking for Redundant Manipulators with Model Uncertainties in Repetitive Tasks
  • RNN based Trajectory Control for Manipulators with Uncertain Kinematic Parameters
  • RNN Based Adaptive Compliance Control for Robots with Model Uncertainties
  • Deep RNN based Obstacle Avoidance Control for Redundant Manipulators .

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