Cross-domain Robot Map Building and Planning in Emergencies
Peng Cheng, Yong kang Liu, Ke Wang · 2021
When a cross-domain mobile robot encounters a variety of emergencies, it needs to quickly plan a new path at the bottom of the controller architecture. The frequency of map construction and planning of traditional robot autonomous systems is low, which cannot meet the real-time requirements of the bottom control system. To solve this problem, a method based on multi-sensor data fusion is proposed to construct a real-time grid map in a complex and multi-emergency environment. This not only achieves a higher map refresh frequency but also enriches the information represented by the map. Then, based on the real-time map, a path planning method combining dynamic window approach (DWA) and safe search strategy is proposed. The feasibility of the designed planning algorithm is verified in simulation and experiment. The algorithm used has a high frequency and gives a path to avoid dangerous conditions, which can meet the real-time planning needs of the bottom control system under emergencies.