This paper conducts a series of case studies on a novel Simultaneous Path and Motion Planning (SiPaMoP) approach [1] to multiple autonomous or Automated Guided Vehicle (AGV) motion coordination in bidirectional networ...This paper conducts a series of case studies on a novel Simultaneous Path and Motion Planning (SiPaMoP) approach [1] to multiple autonomous or Automated Guided Vehicle (AGV) motion coordination in bidirectional networks. The SiPaMoP approach plans collision-free paths for vehicles based on the principle of shortest path by dynamically changing the vehicles’ paths,traveling speeds or waiting times,whichever gives the shortest traveling time. It integrates path planning,collision avoidance and motion planning into a comprehensive model and optimizes the vehicles’ path and motion to minimize the completion time of a set of tasks. Five case studies,i.e.,head-on collision avoidance,catching-up collision avoidance,buffer node generation and collision avoidance,prioritybased motion coordination,and safety distance based planning,are presented. The results demonstrated that the method can effectively plan the path and motion for a team of autonomous vehicles or AGVs,and solve the problems of traffic congestion and collision under various conditions.展开更多
文摘This paper conducts a series of case studies on a novel Simultaneous Path and Motion Planning (SiPaMoP) approach [1] to multiple autonomous or Automated Guided Vehicle (AGV) motion coordination in bidirectional networks. The SiPaMoP approach plans collision-free paths for vehicles based on the principle of shortest path by dynamically changing the vehicles’ paths,traveling speeds or waiting times,whichever gives the shortest traveling time. It integrates path planning,collision avoidance and motion planning into a comprehensive model and optimizes the vehicles’ path and motion to minimize the completion time of a set of tasks. Five case studies,i.e.,head-on collision avoidance,catching-up collision avoidance,buffer node generation and collision avoidance,prioritybased motion coordination,and safety distance based planning,are presented. The results demonstrated that the method can effectively plan the path and motion for a team of autonomous vehicles or AGVs,and solve the problems of traffic congestion and collision under various conditions.
