The practical applicability of controlling swarm robots so that they perform various tasks is gaining traction. The key aspects of this control problem include obstacle avoidance, inter-robot interaction, collision avoidance, and ensuring the orderly movement of robots towards a set goal. This paper proposes a hybrid approach combining Null Space-Based behaviour (NSB) control techniques with logistic map-based chaos theory (C-NSB) in order to enable multi-tasking for swarm robots. When swarm robots need to execute multiple tasks simultaneously, it’s crucial to prioritize the respective tasks. Additionally, this article proposes using the Takagi-Sugeno fuzzy model for estimating the attraction/repulsion forces between the individual robots in a swarm in order to maintain the swarm’s formation. A novel contribution of this paper lies in the introduction of a chaotic variable for facilitating a smoother and more agile robot navigation when a robot is in an area where there is a high risk of collision with an obstacle. The theoretical research results were validated with regard to their correctness and effectiveness through simulations carried out in the Matlab environment.
Behaviour control, Chaos theory, Fuzzy logic, Null space-based behaviour, Swarm robot navigation.
Le Thi Thuy NGA, Van Binh NGUYEN, "Application of Chaos Theory and Null Space-Based Behaviour Control for Swarm Robot Navigation", Studies in Informatics and Control, ISSN 1220-1766, vol. 35(3), pp. 71-80, 2026. https://doi.org/10.24846/v35i3y202607
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