Advanced Sensing and Control Technologies for Autonomous Robots

ISBN 10: 3725831831 / ISBN 13: 9783725831838

Published by MDPI AG, 2025

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - This Reprint compiles cutting-edge research on sensor-driven autonomy and adaptive control strategies for robotic systems operating in dynamic industrial and unstructured environments. It highlights innovations in robust control architectures, such as model-free adaptive control and fault-tolerant MPC frameworks, alongside advancements in perception technologies such as NeoSLAM and TSG-SLAM for dynamic scene navigation. The Reprint's contributions emphasize the synergy of LiDAR-vision-inertial sensor fusion with intelligent decision-making algorithms such as SAC-LSTM path planning while exploring novel paradigms such as artificially empathetic swarm control. By bridging theoretical rigor with industrial implementation, this Reprint provides a vital resource for researchers and engineers advancing resilient robotic autonomy through adaptive control, real-time perception, and multi-agent coordination in logistics, construction, and human-robot collaboration.

Seller Inventory # 9783725831838

Bibliographic Details

• Title: Advanced Sensing and Control Technologies for Autonomous Robots
• Publisher: MDPI AG
• Publication Date: 2025
• Language: English
• ISBN 10: 3725831831
• ISBN 13: 9783725831838
• Binding: Buch
• Condition: Neu
• Dimensions: 250W x 175H x 25D millimeters 250 millimeters width by 175 millimeters height by 25 millimeters depth
• Weight: 1000 grams

About this title

Synopsis

This Reprint compiles cutting-edge research on sensor-driven autonomy and adaptive control strategies for robotic systems operating in dynamic industrial and unstructured environments. It highlights innovations in robust control architectures, such as model-free adaptive control and fault-tolerant MPC frameworks, alongside advancements in perception technologies such as NeoSLAM and TSG-SLAM for dynamic scene navigation. The Reprint's contributions emphasize the synergy of LiDAR-vision-inertial sensor fusion with intelligent decision-making algorithms such as SAC-LSTM path planning while exploring novel paradigms such as artificially empathetic swarm control. By bridging theoretical rigor with industrial implementation, this Reprint provides a vital resource for researchers and engineers advancing resilient robotic autonomy through adaptive control, real-time perception, and multi-agent coordination in logistics, construction, and human-robot collaboration.