Abstract
In this paper, a trajectory optimization method of intelligent is designed. Firstly, genetic algorithm based on genetic evolution is used to get the initial value of the population. Path length, number of turns and energy consumption of the moving manipulator were used as evaluation parameters. A new adjustable crossover and mutation operator is proposed. Finally, genetic algorithm, Artificial bee colony algorithm is used to evaluate the proposed method for trajectory optimization of mobile robots. The results can effectively prevent the local minimum, reduce the time spent in the process of robot movement, and greatly improve the efficiency of the motion trajectory.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Transactions on Computer Science and Intelligent Systems Research
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
