Advanced Autonomous Systems and Artificial Intelligence Stage

ISBN 10: 3725865906 / ISBN 13: 9783725865901

Published by MDPI AG, 2026

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - This Reprint brings together fifteen contributions showcasing recent advances in autonomous systems and artificial intelligence. The collected studies highlight progress in robotics, perception, machine learning, sensor fusion, human-machine interaction, optimization, and data-driven control. The papers cover a wide range of applications, from mobile and assistive robotics to energy management, transportation safety, teleoperation, and intelligent monitoring. Across these studies, a common theme emerges: the shift toward robust, explainable, and human-centered autonomy capable of operating reliably in complex real-world environments. The authors present innovative methodologies that integrate physical modeling with learning-based techniques, enabling stronger adaptability and higher performance. This Reprint provides researchers, engineers, and practitioners with an overview of current directions in intelligent systems and offers valuable insights into emerging challenges, such as trust, safety, interpretability, and sustainable deployment. It reflects the increasing maturity of autonomous technologies and their growing impact on science, industry, and society.

Seller Inventory # 9783725865901

Bibliographic Details

• Title: Advanced Autonomous Systems and Artificial Intelligence Stage
• Publisher: MDPI AG
• Publication Date: 2026
• Language: English
• ISBN 10: 3725865906
• ISBN 13: 9783725865901
• Binding: Buch
• Condition: Neu
• Dimensions: 250W x 175H x 28D millimeters 250 millimeters width by 175 millimeters height by 28 millimeters depth
• Weight: 1129 grams

About this title

Synopsis

This Reprint brings together fifteen contributions showcasing recent advances in autonomous systems and artificial intelligence. The collected studies highlight progress in robotics, perception, machine learning, sensor fusion, human-machine interaction, optimization, and data-driven control. The papers cover a wide range of applications, from mobile and assistive robotics to energy management, transportation safety, teleoperation, and intelligent monitoring. Across these studies, a common theme emerges: the shift toward robust, explainable, and human-centered autonomy capable of operating reliably in complex real-world environments. The authors present innovative methodologies that integrate physical modeling with learning-based techniques, enabling stronger adaptability and higher performance. This Reprint provides researchers, engineers, and practitioners with an overview of current directions in intelligent systems and offers valuable insights into emerging challenges, such as trust, safety, interpretability, and sustainable deployment. It reflects the increasing maturity of autonomous technologies and their growing impact on science, industry, and society.