Direct Optimal Motion Planning for Omni-directional Mobile Robots under Limitation on Velocity and Acceleration

Document Type: Original Manuscript

Authors

1 MSc, Department of Electrical, Biomedical, and Mechatronics Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

2 Associate Professor, Department of Electrical, Biomedical, and Mechatronics Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

Abstract

This paper describes a low computational direct approach for optimal motion planning and obstacle avoidance of Omni-directional mobile robots within velocity and acceleration constraints on the robot motion. The main purpose of this problem is the minimization of a quadratic cost function while limitation on velocity and acceleration of robot is considered and collision with any obstacle in the robot workspace is avoided. This problem can be formulated as a constraint nonlinear optimal control problem. To solve this problem, a direct method is utilized which employs polynomials functions for parameterization of trajectories. By this transforming, the main optimal control problem can be rewritten as a nonlinear programming problem (NLP) with lower complexity. To solve the resulted NLP and obtain optimal trajectories, a new approach with very small run time is used. Finally, the performance and effectiveness of the proposed method are tested in simulations and some performance indexes are computed for better assessment. Furthermore, a comparison between proposed method and another direct method is done to verify the low computational cost and better performance of the proposed method.

Highlights

  • Resulted optimal motion planning is employed for motion planning of the small size soccer robots
  • The velocity and acceleration constraints on the robot motion is considered
  • A direct method is utilized which employs polynomial functions for parameterization of trajectories
  • The optimal control problem (OCP) is converted to nonlinear programming problem (NLP) by using direct method
  • The resulted NLP is solved using a proposed approach with very small run time

Keywords

Main Subjects

Journal of Optimization in Industrial Engineering

Volume 10, Issue 22
Summer and Autumn 2017
Pages 93-101

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