Path Planning Design of Industrial Robots Based on Improved PSO
Algorithm and Artificial Potential Field Method
LI Bin1 ,YANG Haozhong2 ,GAN Xusheng3 ,LI Qi4
Author information+
1. College of Arts, Shangluo University, Shangluo 726000; 2. College of Architecture, Xi’an
University of Architecture and Technology, Xi’an 710055; 3. Air Traffic Control and Navigation
College, Air Force Engineering University, Xi’an 710051; 4. XiJing University, Xi’an 710123
Good path planning can greatly improve the working
efficiency of industrial robots. To solve the problem of
interference judgment between industrial robots and obstacles, an
interference judgment method based on axial angle is proposed.
Combined with interference judgment, the range of the obstacle point
was found and expanded. Based on the improved path planning method
of particle swarm fusion artificial potential field method, the
gravitational field and repulsive force field models are constructed
to generate the initial particle swarm. The traction operation is
proposed to solve the problem that particle swarm optimization is
easy to fall into local optimal. Bessel curve is used for smoothing
operation to solve the problem that path points in grid environment
are too many, which is not conducive to robot walking. An example
shows that this method can overcome the shortcomings of traditional
and intelligent algorithms in robot path planning, and it has strong
searching ability and convergence ability.
LI Bin, YANG Haozhong, GAN Xusheng, LI Qi.
Path Planning Design of Industrial Robots Based on Improved PSO
Algorithm and Artificial Potential Field Method. Journal of Systems Science and Mathematical Sciences, 2021, 41(4): 939-952 https://doi.org/10.12341/jssms20270