Real-time Motion Planning Based on Layered Cost Map for AGV Navigation
Huifang Kong, Jixing Sun, Jie Hu · 2020
A motion planning method that integrates global planning and local control is proposed in this paper, aiming to enable Automated Guided Vehicle (AGV) to navigate automatically in two-dimensional environment. The layered cost maps are utilized and divided into global cost map and local cost map to respectively provide environment information for the global planning and local control. Specifically, the global planning is based on the path planning algorithm to establish a global optimal path on the global cost map. Under the guidance of global path, local control generates an optimal collision free trajectory with temporal information on the local cost map, which can avoid contact with surrounding obstacles. The local control operates in real-time and consider temporal information, thereby it can directly generate commands for the underlying robot motion controller. Both the simulation and experimental results are presented in support of the feasibility and effectiveness of the proposed motion planning.