Proceedings of 3rd 2023 International Conference on Autonomous Unmanned Systems (3rd ICAUS 2023)

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.

Presents the proceedings of ICAUS 2023 Covers a range of emerging topics in unmanned systems, robotics A reference resource for a broad and diverse readership

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Inhalt

Chapter 1. Collision-Free UAV Flocking System with Leader-guided Cucker-Smale Reward Based on Reinforcement Learning.- Chapter 2. A Task Allocation Algorithm of Loitering Munition Group for Regional Blockade based on Event-driven.- Chapter 3. Research on the Dilemma and Strategy of Training Applied Talents in UAV Specialty.- Chapter 4. Design and Implementation of Terrain following Algorithm for Cruise Missile.- Chapter 5. Task Assignment Algorithm for Unmanned Systems Based on Step Clustering Ant Colony.- Chapter 6. A Neural Network-Based Adaptive Dynamic Surface Control for Nonlinear Systems in Strict-Feedback Form with Input Constraints.- Chapter 7. TAMPI: A Time-Aware Multi-Perspective Interaction Framework for Temporal Knowledge Graph Completion.- Chapter 8. Lightweight Multimodal Fusion for Autonomous Navigation via Deep Reinforcement Learning.- Chapter 9. A Scalable Multi-Agent Reinforcement Learning Approach Based on Value function Decomposition.- Chapter 10. A GeneralizableAutonomous Maneuvering Decision-Making Method for UCAV Air Combat Combining PER-D3QN and Zero-Sum Markov Game, etc. <p