Abstract:
An innovative approach to UAV trajectory planning is introduced through the utilization of an adaptive potential field ant colony algorithm. This method enhances initial-...View moreMetadata
Abstract:
An innovative approach to UAV trajectory planning is introduced through the utilization of an adaptive potential field ant colony algorithm. This method enhances initial-stage search efficiency by refining adaptive state transition rules. By integrating the initial trajectory from the artificial potential field method alongside distance data for subsequent nodes, heuristic information optimization is employed to circumvent local extrema. Concurrently, the introduction of a heuristic information attenuation coefficient serves to diminish the influence of heuristic data. Dynamically modify pheromone update rules to enhance initial global search, expedite mid to late-stage convergence, and maintain trajectory diversity. Simulation results confirm the algorithm's feasibility and efficacy.
Published in: 2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS)
Date of Conference: 22-24 September 2023
Date Added to IEEE Xplore: 03 November 2023
ISBN Information: