Energy-Optimal 3D Path Planning for MAV with Motion Uncertainty. (18th October 2021)

• Record Type: Journal Article
• Authors: Li, Yamin; Sun, Bowen; Xia, Ping; Yang, Yang
• Other Names: Liu Guanfeng Academic Editor.
• Is Part Of: Complexity. Volume 2021(2021)
• Publication Date: 2021-10-18
• Subjects: Chaotic behavior in systems -- Periodicals; Complexity (Philosophy) -- Periodicals; 003
• DOI: 10.1155/2021/9994680
• Languages: English
• ISSNs: 1076-2787

Abstract

Abstract : Practical applications of microaerial vehicle face significant challenges including imprecise localization, limited on-board energy, and motion uncertainty. This paper focuses on the latter two issues. The core of proposed energy-optimal path planning algorithm is an energy consumption model deriving from real measurements of a specific quadrotor and utilizing a 2D Gaussian distribution function to simulate the uncertainty of random drift. Based on these two models, we formulate the optimal path traversing the 3D map with minimum energy consumption using a heuristic ant colony optimization. Multiple sets of contrast experiments demonstrate the effectiveness and efficiency of the proposed algorithm.