TY - GEN
T1 - A Slope-Adaptive Navigation Approach for Ground Mobile Robots
AU - Hu, Biao
AU - Cui, Mingyue
AU - Cao, Zhengcai
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The 2-dimensional cost map has been widely used for the navigation of ground mobile robot. Although it is effective when the ground is flat, it becomes clumsy and ineffective when the ground has some slopes, where such slopes are often misjudged as the forbidden area by the cost map. For this reason, we propose a slope-adaptive navigation approach based on multilayer cost map in this paper. Instead of taking the point cloud of slope as obstacles, we actively construct a multi-layer cost map that takes slope information into the map in the stage of building environment map. A slope detection algorithm is developed to switch the cost map during the robot navigation. The slope is then considered as a passable road, only with extra cost. In the case that the slope leads the robot to a new floor, we adopt the Aruco code to switch the map information, such that the navigation can still keep working. Both simulation and real-world experimental results demonstrate the high effectiveness of our proposed approach.
AB - The 2-dimensional cost map has been widely used for the navigation of ground mobile robot. Although it is effective when the ground is flat, it becomes clumsy and ineffective when the ground has some slopes, where such slopes are often misjudged as the forbidden area by the cost map. For this reason, we propose a slope-adaptive navigation approach based on multilayer cost map in this paper. Instead of taking the point cloud of slope as obstacles, we actively construct a multi-layer cost map that takes slope information into the map in the stage of building environment map. A slope detection algorithm is developed to switch the cost map during the robot navigation. The slope is then considered as a passable road, only with extra cost. In the case that the slope leads the robot to a new floor, we adopt the Aruco code to switch the map information, such that the navigation can still keep working. Both simulation and real-world experimental results demonstrate the high effectiveness of our proposed approach.
KW - layered cost map
KW - navigation
KW - target detection
UR - https://www.scopus.com/pages/publications/85142672263
U2 - 10.1109/SMC53654.2022.9945551
DO - 10.1109/SMC53654.2022.9945551
M3 - 会议稿件
AN - SCOPUS:85142672263
T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
SP - 610
EP - 615
BT - 2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022
Y2 - 9 October 2022 through 12 October 2022
ER -