Robot Swarm Collaboration in the Unstructured Environment

Dear Colleagues,

Multi-robot systems play a crucial role in human life due to their diverse functionalities, high flexibility, and strong scalability. Nevertheless, as intelligent transformation advances, robots operating in typical, structured environments are no longer adequate to meet the complex, dynamic, and ever-changing application demands. In unstructured environments, robots must utilize multiple sensors to enable them to collaborate and communicate with each other in groups. Therefore, how to enhance the swarm collaboration capabilities of robots is an urgent and important issue that needs to be discussed.

The objective of this Special Issue is to compile the latest studies on the autonomous operation of robots in unstructured environments. This compilation aims to enhance the application and deployment of autonomous robots in future fields such as industrial, medical, agricultural, etc. On the one hand, the rapid development of artificial intelligence technologies (e.g., reinforcement learning and transfer learning) has significantly advanced the autonomous perception and learning capabilities of robots. On the other hand, the further evolution of learning and swarm intelligence models has successfully enabled the application of interaction between groups of robots in various fields. These technologies promote the development of individual robots and help to expand the potential applications of intelligent swarm robots.

This Special Issue aims to demonstrate the latest technical developments in individual behavior and swarm intelligence from the perspective of intelligent robots based on multiple sensors. We welcome innovative contributions in the form of original research articles, reviews, opinion papers, perspectives, and papers on novel methods for evolving robot behavior.

Contributions include, but are not limited to, the following:

1. Robot environment perception based on multiple sensors;
2. Robot target detection based on multiple sensors;
3. Robot autonomous planning based on multiple sensors;
4. Robot skill learning based on multiple sensors;
5. Multi-sensor-based swarm robot collaboration;
6. Self-decision-making of swarm robots based on multiple sensors;
7. Intelligent cooperative behavior of human–robot;
8. Blockchain-based wireless communication within robotic swarms;
9. Cybersecurity of the robot swarm collaboration.

Dr. Qingsong Fan
Prof. Dr. Haisong Huang
Dr. Yung Po Tsang
Guest Editors

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