Overview

This book includes original, peer-reviewed research papers from the 3rd ICAUS 2023, which provides a unique and engaging platform for scientists, engineers and practitioners from all over the world to present and share their most recent research results and innovative ideas. The 3rd ICAUS 2023 aims to stimulate researchers working in areas relevant to intelligent unmanned systems. Topics covered include but are not limited to: Unmanned Aerial/Ground/Surface/Underwater Systems, Robotic, Autonomous Control/Navigation and Positioning/ Architecture, Energy and Task Planning and Effectiveness Evaluation Technologies, Artificial Intelligence Algorithm/Bionic Technology and their Application in Unmanned Systems. The papers presented here share the latest findings in unmanned systems, robotics, automation, intelligent systems, control systems, integrated networks, modelling and simulation. This makes the book a valuable resource for researchers, engineers and students alike.

Full Product Details

Author:   Yi Qu ,  Mancang Gu ,  Yifeng Niu ,  Wenxing Fu
Publisher:   Springer Verlag, Singapore
Imprint:   Springer Nature
Edition:   1st ed. 2024
Volume:   1177
ISBN:  

9789819711024

ISBN 10:   9819711029
Pages:   493
Publication Date:   27 April 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Chapter 1. A personalized ramp merging decision-making method for autonomous driving based on reverse reinforcement learning.- Chapter 2. An adaptive cruise hybrid control method for unmanned driving.- Chapter 3. Dynamic Quantitative Analysis for Large Scale Skid-steered UGV.- Chapter 4. An Optimization-based Path Planning Method for Unmanned Systems in Multi-obstacle Environments.- Chapter 5. An adaptability-based terrain costmap for heterogeneous vehicle swarm path planning.- Chapter 6. Attention encoder-decoder network based autonomous risk driving identification for connected heavy-duty vehicles.- Chapter 7. Loosely-coupled Camera-IMU-OGS fusion Localization.- Chapter 8. Multi-sensing pedestrian detection method based on an improved EPNet.- Chapter 9. Abrupt Lane Change Recognition Model Towards Autonomous Vehicle based on Lane Line Inclination.- Chapter 10. Path-oriented Green Wave Speed Control Model Towards Autonomous Vehicle, etc.

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