Advanced Intelligent Control in Robots

Edited by
July 2023
452 pages
  • ISBN978-3-0365-8148-4 (Hardback)
  • ISBN978-3-0365-8149-1 (PDF)

This book is a reprint of the Special Issue Advanced Intelligent Control in Robots that was published in

Chemistry & Materials Science
Environmental & Earth Sciences

Advanced intelligent control is a rapidly developing, complex and challenging field with significant practical importance and potential applications. The authors aim to stimulate advancements in science and technology by addressing this field and presenting new trends in the design, control and applications of real-time intelligent sensor system control using advanced intelligent control methods and techniques. The purpose of the Special Issue is to promote in-depth research and communication regarding these topics. The authors focus on innovative multi-sensor fusion techniques integrated into robots, which are combined with computer vision, virtual and augmented reality (VR&AR) and intelligent communication including remote control, adaptive sensor networks and human–robot (H2R) interaction systems. Special attention is given to advancements in sensors, actuators, computation technology and communication networks that provide the necessary tools for implementing intelligent control hardware. These advancements are targeted toward various scientific research fields, including machine learning (such as deep learning), bio-inspired algorithms, recurrent neural networks, neuro-fuzzy control and artificial intelligence in general. The Special Issue includes original research papers that report on the recent advancements in intelligent control using intelligent sensors. It serves as a further extension of the previously successful Special Issue, “Advanced Intelligent Control through Versatile Intelligent Portable Platforms”.

  • Hardback
License and Copyright
© 2022 by the authors; CC BY-NC-ND license
nonlinear intelligent control; support vector regression; feedforward control; human arm viscoelastic; resource-aware control; co-regulation; feedback scheduling; time-varying system; neural adaptive control; fault-tolerant control; integrated attitude and position control; spacecraft proximity operations; indirect neural approximation; Lyapunov analysis; real-time trajectory prediction; mechanically thrown objects; internal logistics; smart manufacturing systems; multi-camera simulation; many-to-many time series forecasting; encoder-decoder bidirectional LSTM deep neural networks; arbitrary order sliding mode; networked system; finite-time systems; nonlinear system; hybrid position/force control; sliding mode control; decision method; neutrosophic logic; extension set; mobile robot; advanced intelligent control; wheeled–legged; trajectory tracking; model predictive control; smart vehicle; probabilistic roadmap algorithm; pseudo-random sampling; collision detection; path smoothing; monocular vision; human joint angle measurement; visual detection method; hand disability; mobile manipulator; motion planning; simultaneous control; path analysis; ROS; rehabilitation robot; human–robot interaction; admittance control; robust control; active strength training; sEMG; lower limb rehabilitation robot; compliance control; training mode; MOTOmed; continuous passive motion; straight leg raise; feature analysis; wire + arc additive manufacturing; surface roughness; deep neural network; arc welding; quadruped robot; change of running direction; dynamic model; stability index system; simulation analysis; self-collision detection; dual-manipulator system; artificial intelligence; deep neural network; GJK algorithm; robotics control; local path planner; task redundancy; collision avoidance strategy; human–robot interaction; drone; UAV; multi-agent; ArUco; markers; group of drones; machine vision; computer vision; sensors; machine learning; industry; manufacturing; robotics; sensor systems; remote control and communication; UAV; simulation; artificial intelligence; mobile health; stroke monitoring; iomt-stacked convolutional neural networks; GMDH neural networks; Deep LSTM; biomedical EMG signal processing; rapidly-exploring random tree (RRT); path planning; robot manipulator; object pick-and-place; collision-free; robot operating system (ROS); n/a