Vectorization path planning for autonomous mobile agent in unknown environment
This paper presents a novel real-time path planning algorithm, called InsertBug, for an autonomous mobile agent in completely unknown environment. By using the algorithm, all the planned paths are described and stored by vectors. The algorithm combines range sensor data with safety radius to determine the blocking obstacles and calculate the shortest path by choosing the intermediate points. When there is obstacle blocking the current path, the intermediate points will be calculated, and the planned path will be regenerated by inserting the intermediate points. The local optimum avoidance strategy is also considered in this algorithm by specifying a fixed direction. The agent will return to the optimal direction after running out of the local optimum. Different simulation parameters are taken to show the advantages of this algorithm. Moreover, the performance of this algorithm has also been evaluated by comparing with another usual method via simulations. The results show that the safety performance and time requirements of this algorithm are significant superior to the algorithm contrasted with.
vectorization path path planning unknown environment bug algorithm