PSO-based Minimum-time Motion Planning for Multiple Vehicles Under Acceleration and Velocity Limitations
Autor: | Anugrah K. Pamosoaji, Keum-Shik Hong, Mingxu Piao |
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Rok vydání: | 2019 |
Předmět: |
0209 industrial biotechnology
Computer science Industri Particle swarm optimization State vector 02 engineering and technology Maximization Computer Science Applications Constant linear velocity Acceleration 020901 industrial engineering & automation Control and Systems Engineering Control theory Search algorithm Motion planning Minification |
Zdroj: | International Journal of Control, Automation and Systems. 17:2610-2623 |
ISSN: | 2005-4092 1598-6446 |
DOI: | 10.1007/s12555-018-0176-9 |
Popis: | This paper discusses a particle swarm optimization (PSO)-based motion-planning algorithm in a multiple-vehicle system that minimizes the traveling time of the slowest vehicle by considering, as constraints, the radial and tangential accelerations and maximum linear velocities of all vehicles. A class of continuous-curvature curvesthree-degree Bezier curvesis selected as the basic shape of the vehicle trajectories to minimize the number of parameters required to express them mathematically. In addition, velocity profile generation using the local minimum of the radial-accelerated linear velocity profile, which reduces the calculation effort, is introduced. A new PSO-based search algorithm, called “particle-group-based PSO,” is introduced to find the best combination of trajectories that minimizes the traveling time of the slowest vehicle. A particle group is designed to wrap a set of particles representing each vehicle. The first and last two control points characterizing a curve are used as the state vector of a particle. Simulation results demonstrating the performance of the proposed method are presented. The main advantage of the proposed method is its minimization of the velocity-profile-generation time, and thereby, its maximization of the search time. |
Databáze: | OpenAIRE |
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