Abstract
This work presents a novel path-planning approach for Unmanned Aerial Vehicles (UAVs) in continuous 3D environments. This proposal aims to minimize the path length while avoiding collisions through the suitable adjusting of control points (the points that take the UAV from a start position to a target location). The above is stated as a constrained global optimization problem. This problem considers the overall length of the path as the single objective function. Regarding the problem constraints, they are related to the collision of the obstacles with the 3D shape of a path. The assignment of the path shape is also proposed in this work to streamline the planning process. Due to the optimization problem features (high nonlinearity, multimodality, non-differentiability, and the lack of an initial guess solution), a constraints-handling mechanism is used in meta-heuristics to find suitable optimized paths. Also, an enhanced path-search mechanism is included in these algorithms to deal with complex planning scenarios. The enhanced mechanism incorporates a path computed by a variant of the A-Star method (the Pruned A-Star) in the first set of candidate solutions of the meta-heuristics. The proposed approach is tested through six complex scenarios. Moreover, the performance of three well-known meta-heuristics, Differential Evolution (DE), Particle Swarm Optimization (PSO), and the Genetic Algorithm (GA), is studied to find a potential candidate to solve the path-planning problem. In this way, the paths found by DE show outstanding performance. The paths obtained by the Pruned A-Star technique are adopted as a point of comparison to determine the advantages and drawbacks of the proposal.
Highlights
Autonomy is a highly desirable feature of robots because it endows them with skills to perform complex tasks with minimal human intervention [1].In the context of mobile robotics, motion planning is one of the most challenging problems due to the large number of issues that need to be addressed
The issues related to motion planning of mobile robots include environment perception, The associate editor coordinating the review of this manuscript and approving it for publication was Bijoy Chand Chand Chatterjee
For this Unmanned Aerial Vehicles (UAVs), its container Oriented Bounding Boxes (OBBs) dimension is set as du = [0.175, 0.24, 0.065]T (m) to allow short-range maneuvers
Summary
Autonomy is a highly desirable feature of robots because it endows them with skills to perform complex tasks with minimal human intervention [1]. In the context of mobile robotics, motion planning is one of the most challenging problems due to the large number of issues that need to be addressed. The issues related to motion planning of mobile robots include environment perception, The associate editor coordinating the review of this manuscript and approving it for publication was Bijoy Chand Chand Chatterjee. Localization, map building, recognition, path-planning, and motion control [2]. The motion planning is used to determine how a robot must move to perform a task successfully. In the case of localization and map building, they determine the current position of the mobile robot regarding its environment [2].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
