2019 ◽  
Vol 16 (4) ◽  
pp. 172988141986038
Author(s):  
Huang Yiqing ◽  
Wang Hui ◽  
Wei Lisheng ◽  
Gao Wengen ◽  
Ge Yuan

This article presented a cooperative mapping technique using a novel edge gradient algorithm for multiple mobile robots. The proposed edge gradient algorithm can be divided into four behaviors such as adjusting the movement direction, evaluating the safety of motion behavior, following behavior, and obstacle information exchange, which can effectively prevent multiple mobile robots falling into concave obstacle areas. Meanwhile, a visual field factor is constructed based on biological principles so that the mobile robots can have a larger field of view when moving away from obstacles. Also, the visual field factor will be narrowed due to the obstruction of the obstacle when approaching an obstacle and the obtained map-building data are more accurate. Finally, three sets of simulation and experimental results demonstrate the performance superiority of the presented algorithm.


Author(s):  
JUAN ANDRADE-CETTO ◽  
ALBERTO SANFELIU

A system that builds and maintains a dynamic map for a mobile robot is presented. A learning rule associated to each observed landmark is used to compute its robustness. The position of the robot during map construction is estimated by combining sensor readings, motion commands, and the current map state by means of an Extended Kalman Filter. The combination of landmark strength validation and Kalman filtering for map updating and robot position estimation allows for robust learning of moderately dynamic indoor environments.


Sign in / Sign up

Export Citation Format

Share Document