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Optimal path planning for two-wheeled self-balancing vehicle pendulum robot based on quantum-behaved particle swarm optimization algorithm

  • Qingwen Qian
  • Junfeng WuEmail author
  • Zhe Wang
Original Article

Abstract

Based on the self-balance of free-floating two-wheel self-balancing pendulum robot system, an optimal path planning of two-wheel self-balancing pendulum robot is proposed. Firstly, the corner trajectory of the two-wheel self-balancing pendulum robot is parameterized by quantum particle swarm optimization (QPSO), and the objective function is designed according to the base attitude and the control accuracy of the robot’s terminal position and attitude. The optimal path planning problem of the two-wheel self-balancing pendulum robot system is transformed into the optimization problem of the non-linear system. Quantum particle swarm optimization (QPSO) algorithm is used to solve the non-linear optimization problem, and the goal of optimal path planning is achieved. The experimental results show that the proposed method can converge to the global optimal value with fast convergence speed and less adjustment parameters. The planned joint path satisfies the range of corner, angular velocity, and angular acceleration. The joint path is smooth and suitable for the control of two-wheel self-balancing pendulum robot.

Keywords

Two-wheeled self-balancing vehicle pendulum robot Optimal path planning Quantum-behaved particle swarm optimization Posture adjustment 

Notes

Funding information

This work was financially supported by Science and Technology Innovation Talents Special Foundation of Harbin (no. 2014RFXXJ051); open research project of Anhui simulation design and modern manufacture engineering technology research center (no. SGCZXYB02); Science and Technology Innovation Talents Special Foundation of Harbin (outstanding academic leaders) (no. 2014RFXXJ051).

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.College of Automation Harbin University of Science and TechnologyHarbinChina
  2. 2.College of Mechanical and Electrical EngineeringHuangshan UniversityHuangshanChina

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