A Quantum-Based Collaborative Guidance Strategy for Multi-Robot Plume Source Localization

TL;DR: A quantum-based collaborative guidance strategy for multi-robot plume source localization effectively addresses the issue of source localization in the presence of obstacles and communication restrictions. The strategy utilizes information fusion, path planning, swarm evolutionary mechanisms, and quantum potential wells to guide robots toward the plume source.

Abstract: In combination with optimization theory and swarm evolutionary mechanisms, based on multiple mobile robots equipped with sensors, this article deals with a plume source localization issue with information fusion, environmental obstacles, and communication restrictions for robots. First of all, combined with information fusion, in terms of collision avoidance and communication restrictions between robots, the source localization issue can be addressed by solving a path planning one with constraints for cooperative swarm robots, which is transformed into an unconstrained one by an information penalty policy. Second, after a quantum potential well is coupled, two pairs of average estimators and minimum estimators are introduced into swarm evolutionary mechanisms with a knowledge-driven protocol and an adjustable oscillation weight, and the distributed quantum-inspired guidance (DQIG) strategy as a guidance scheme is proposed to drive the robots toward the plume source. Subsequently, we put forth a formation behavior consisting of leader–follower mechanisms, obstacle avoidance mechanisms, motion optimization mechanisms and target encircling mechanisms, which not only provides a practical collision/obstacle measure, but also increases the coverage area for the target. Afterward, a performance analysis for the proposed policy is executed on the convergence and computational complexity, which ensures the accuracy and timeliness of the source localization in theory. Ultimately, simulation verification is carried out, and the results validate the practicability and effectiveness of the developed method.