Combining particle filter algorithm with bio-inspired anemotaxis behavior: A smoke plume tracking method and its robotic experiment validation

摘要

The smoke source localization robot is a safe substitution of human and animal rescuers in many dangerous search and rescue mission. In this paper, we propose an anemotaxis - particle filter based smoke plume path tracking method and presented a smoke source localization robot. A modified firefly algorithm is applied in the resampling step of particle filter based smoke plume tracking method to mimic anemotaxis behaviors in the odor source searching process of living creatures. The performance of the proposed algorithm is qualitatively evaluated in a simulated wind tunnel environment in Webots, a high-fidelity robotic simulator. The average computation time including plume path estimation, resampling and target evaluation in every step is 35.9974 ms and the average smoke source localization error is 0.7769 m. We also verify the feasibility by running the proposed algorithm on the smoke source localization robot in real experiments. (C) 2020 Elsevier Ltd. All rights reserved.