Escaping Local Minima in Path Planning Using a Robust Bacterial Foraging Algorithm

Applied Sciences

Ahmet Güneş¹  Deepti Mishra²  MohammedIsam Ismael Abdi³  MuhammadUmer Khan³ 

[1] Defense Technologies Institute, Gebze Technical University, Kocaeli 41400, Turkey;Department of Computer Science, Norwegian University of Science and Technology (NTNU), 2815 Gjøvik, Norway;Department of Mechatronics Engineering, Atilim University, Ankara 06830, Turkey;

关键词: mobile robots;    path planning;    bacterial foraging optimization;    local minima;    information sharing;    swarm robots;   

DOI  :  10.3390/app10217905

来源: DOAJ

【 摘 要 】

The bacterial foraging optimization (BFO) algorithm successfully searches for an optimal path from start to finish in the presence of obstacles over a flat surface map. However, the algorithm suffers from getting stuck in the local minima whenever non-circular obstacles are encountered. The retrieval from the local minima is crucial, as otherwise, it can cause the failure of the whole task. This research proposes an improved version of BFO called robust bacterial foraging (RBF), which can effectively avoid obstacles, both of circular and non-circular shape, without falling into the local minima. The virtual obstacles are generated in the local minima, causing the robot to retract and regenerate a safe path. The proposed method is easily extendable to multiple robots that can coordinate with each other. The information related to the virtual obstacles is shared with the whole swarm, so that they can escape the same local minima to save time and energy. To test the effectiveness of the proposed algorithm, a comparison is made against the existing BFO algorithm. Through the results, it was witnessed that the proposed approach successfully recovered from the local minima, whereas the BFO got stuck.

【 授权许可】

Unknown