In this paper, we present a new method for a swarm to collectively sense and follow a gradient in the environment. The agents in the swarm only rely on relative distance and bearing measurements of neighbors. Additionally, only a minority of agents in the swarm perceive the scalar value of the gradient at their location. We test the method with incrementally changing ratio of agents with sensors on various swarm sizes. In addition to repeated simulation experiments, we also test the performance with a real nano-drone swarm. Results show us that, using the new method, the swarm was successful at following the gradient in the environment even with a low portion of the swarm with sensors on various swarm sizes. A real nano-drone swarm also demonstrates a good performance in our test even with members having disabled sensors.
Collective Gradient Following with Sensory Heterogeneous UAV Swarm
Springer Proceedings in Advanced Robotics
International Symposium on Distributed Autonomous Robotic Systems ; 2022 ; Montbéliard, France November 28, 2022 - November 30, 2022
2024-02-01
15 pages
Aufsatz/Kapitel (Buch)
Elektronische Ressource
Englisch
Stable Belief Estimation in Shepherd-Assisted Swarm Collective Decision Making
Springer Verlag | 2021
|Towards a Heterogeneous Swarm for Object Classification
IEEE | 2019
|Formation tracking control for heterogeneous swarm systems
TIBKAT | 2022
|