Smooth trajectory planning for robot using Particle Swarm Optimization

R. Menasri 1 H. Oulhadj 2 B. Daachi 1 A. Nakib 2 P. Siarry 2
1 SIRIUS
LISSI - Laboratoire Images, Signaux et Systèmes Intelligents
2 SIMO
LISSI - Laboratoire Images, Signaux et Systèmes Intelligents
Abstract : In this work, we deal with a class of problems of trajectory planning taking into account the smoothness of the trajectory. We assume that we have a set of positions in which the robot must pass. These positions are not assigned in the time axis. In this work, we propose a formulation of this problem, where the total length of the trajectory and the total time to move from the initial to the final position are minimized simultaneously. In order to ensure effective results and avoid abrupt movement, we should ensure the smoothness of the trajectory not only at the position level but also at the velocity and the acceleration levels. Thus, the position function must be at least two times differentiable. In our case, we use a polynomial function. We formulate this problem as a constraint optimization problem. To resolve it, we adapt the usual particle swarm algorithm to our problem and we show its efficiency by simulation.
Keywords : Trajectory planning Smooth trajectory Particle swarm optimization
Type de document :
Chapitre d'ouvrage
P. Siarry and L. Idoumghar and J. Lepagnot. Swarm Intelligence Based Optimization: Revised Selected Papers of the first International Conference, ICSIBO 2014, Mulhouse, France, May 13-14, 2014, France, Lecture Notes in Computer Science series, Subseries: Theoretical Computer Science and General Iss, Springer, pp.50-59, 2014
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https://hal.archives-ouvertes.fr/hal-01682090
Contributeur : Lab Lissi <>
Soumis le : jeudi 11 janvier 2018 - 23:47:53
Dernière modification le : dimanche 27 janvier 2019 - 11:43:35

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R. Menasri, H. Oulhadj, B. Daachi, A. Nakib, P. Siarry. Smooth trajectory planning for robot using Particle Swarm Optimization. P. Siarry and L. Idoumghar and J. Lepagnot. Swarm Intelligence Based Optimization: Revised Selected Papers of the first International Conference, ICSIBO 2014, Mulhouse, France, May 13-14, 2014, France, Lecture Notes in Computer Science series, Subseries: Theoretical Computer Science and General Iss, Springer, pp.50-59, 2014. 〈hal-01682090〉

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