Local Path Planning Using CA Model to Avoid Transient Obstacles for Robotic on Hospital Corridor

Abstract

Obstacle avoidance is currently treated by methods that fall into two broad categories, global and local. In this paper, we consider the case that the environment contains obstacles whose speed and direction cannot be predicted. To avoid such kind of obstacles, we introduce a local path planning methodology for a robotics by using Cellular Automata model. This local path planning was combined with Dijkstra shortest path algorithm as global path planning to obtain an optimal route. Using the proposed methodology, a scene in a typical hospital corridor has been created. By using CA model, we evaluated two kinds of obstacle avoidance movement. First, the robotic use the "stop and go" method, which is the robotic will decrease its speed while encounter a transient obstacle. The second one is detour model, in which the robotic will make a detour motion to avoid a transient obstacle. The simulation results show that in dynamic environment that having transient obstacles, the "stop and go" method produced minimal collision with shortest-distance path. While, using the detour model generated minimal collision with time-minimal navigation path.