Integrated Global and Local Path Planning for Quadrotor Using Particle Swarm Optimization. Issue 2 (2020)

• Record Type: Journal Article
• Authors: Hong, Youkyung; Kim, Suseong; Cha, Jihun
• Is Part Of: IFAC-PapersOnLine. Volume 53:Issue 2(2020)
• Page Start: 15621
• Page End: 15625
• Publication Date: 2020
• Subjects: Quadrotor -- Path Planning -- Particle Swarm Optimization -- Minimum Snap Trajectory; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2020.12.2497
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: This study proposes a new path planning method for quadrotors to determine a set of waypoints by considering both geometric constraints to avoid collisions with obstacles and dynamic constraints to reflect the dynamic characteristics of the quadrotor. The proposed path planning method can be formulated as a non-linear optimization problem that minimizes the Euclidean distance between waypoints while satisfying the geometric and dynamic constraints. Particle swarm optimization is utilized to solve the non-linear optimization problem efficiently. By utilizing the Gazebo simulator, the performance of the proposed path planning method is validated for a quadrotor.