Navigation method of fire-fighting robot based on a commercial electronic map
Zehua Chen, Qitao Tang, Xiaohui Kuo, Zhejun Miao, Shuang Liu · 2022 IEEE International Conference on Robotics and Biomimetics (ROBIO) · 2022
As fire-fighting robots perform emergency tasks in an outdoor long-distance environment such as urban fire rescue, a global prior map is hard to be obtained, so most fire-fighting robots are remotely controlled by humans to reach the target location. To solve this problem, we propose a navigation method based on a commercial electronic map like the 2D AutoNavi map (knowns as Gaode in Chinese), which can plan rough sub-target points to guide local motion planning. Global planner uses the commercial electronic map API to plan rough global sub-target points and then aligns the global sub-target points data with the real positioning information. In the local grid map, the local planner performs local planning tasks in order of sub-target points. During the local movement, the sub-target point of each segment is corrected in real time according to the actual environmental information. Extensive experiments have been carried out in outdoor environment. The results prove that this method has better real-time performance for fire-fighting robots' outdoor navigation and is easy to deploy with no prior map.