TY - GEN
T1 - How Do Robot Swarms Behave Compliantly?
AU - Zhang, Xiaozhen
AU - Zhao, Zeming
AU - Yang, Qingkai
AU - Fang, Hao
AU - Chen, Jie
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Conflicts often arise in swarm robotics between individual tasks related to environmental adaptation and the cooperative objective of maintaining a formation. For instance, obstacles may prevent robots from achieving a prescribed formation. Individual tasks, such as collision avoidance, are typically more urgent than the formation maintenance objective. As a result, it is necessary for the formation to compromise (i.e., be compliant) with these individual tasks, highlighting the need for swarm robots to behave compliantly. Inspired by the action principle of compliant control in physical robots, this paper proposes a distributed method that endows swarm robots with compliance. From the perspective of an individual robot, the method enables each robot to achieve its local tasks, allowing it to adapt to its environment. At the swarm level, the approach facilitates a compromise between formation maintenance and individual tasks, mitigating conflicts between individuality and collective objectives. Consequently, the swarm behaves compliantly, autonomously adjusting its formation shape. Finally, experimental results demonstrate the effectiveness of the proposed method, showing its ability to enhance the flexibility and adaptability of swarm formations.
AB - Conflicts often arise in swarm robotics between individual tasks related to environmental adaptation and the cooperative objective of maintaining a formation. For instance, obstacles may prevent robots from achieving a prescribed formation. Individual tasks, such as collision avoidance, are typically more urgent than the formation maintenance objective. As a result, it is necessary for the formation to compromise (i.e., be compliant) with these individual tasks, highlighting the need for swarm robots to behave compliantly. Inspired by the action principle of compliant control in physical robots, this paper proposes a distributed method that endows swarm robots with compliance. From the perspective of an individual robot, the method enables each robot to achieve its local tasks, allowing it to adapt to its environment. At the swarm level, the approach facilitates a compromise between formation maintenance and individual tasks, mitigating conflicts between individuality and collective objectives. Consequently, the swarm behaves compliantly, autonomously adjusting its formation shape. Finally, experimental results demonstrate the effectiveness of the proposed method, showing its ability to enhance the flexibility and adaptability of swarm formations.
UR - https://www.scopus.com/pages/publications/105016227240
U2 - 10.1109/ICCA65672.2025.11129731
DO - 10.1109/ICCA65672.2025.11129731
M3 - Conference contribution
AN - SCOPUS:105016227240
T3 - IEEE International Conference on Control and Automation, ICCA
SP - 648
EP - 655
BT - 2025 IEEE 19th International Conference on Control and Automation, ICCA 2025
PB - IEEE Computer Society
T2 - 19th IEEE International Conference on Control and Automation, ICCA 2025
Y2 - 30 June 2025 through 3 July 2025
ER -