Abstract
Yang and Meng (2000) proposed a biologically inspired neural network model for robot trajectory generation. The generated robot path in a static environment is optimal in the sense of the shortest robot path, which is demonstrated by descriptive analysis and simulations studies, without any rigorous theoretical analysis on the optimality. In this paper, theoretical analysis of the global stability of the neural network system is presented. In addition, the shortest path in a static environment is rigorously proved, and the condition resulting in an optimal solution is formulated. Two case studies of path planning in static and dynamic environments are conducted to demonstrate the effectiveness of the algorithm.
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 callDisclaimer: 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.
