Title :
Kalman filter and vision localization based potential field method for autonomous mobile robots
Author :
Zhang, Le-Jie ; Hou, Zeng-Guang ; Tan, Min
Author_Institution :
Lab. of Complex Syst. & Intelligence Sci., Chinese Acad. of Sci., Beijing, China
Abstract :
In this paper, artificial potential field is utilized for autonomous mobile robot (AMR) path planning in dynamic uncertain environment. First, in order to obtain the repulsive force from the obstacles, sonar data are used in the AMR system to acquire the distance between the AMR and obstacles. And an improved Kalman filter is proposed in this paper to eliminate the sonar signal´s disturbance due to the environmental noise. Then, by taking advantage of vision localization based on polynomial fitting, the attractive force towards the goal is obtained. The effectiveness of the proposed method for the AMR path planning is verified by experiments performed on the mobile robot, CASIA-1.
Keywords :
Kalman filters; collision avoidance; mobile robots; polynomials; robot vision; signal denoising; sonar signal processing; CASIA-1 mobile robot; Kalman filter; artificial potential field; attractive force; autonomous mobile robot path planning; dynamic uncertain environment; environmental noise; polynomial fitting; repulsive force; sonar data; sonar signal disturbance elimination; vision localization based potential field method; Artificial intelligence; Cameras; Mobile robots; Navigation; Path planning; Polynomials; Robot kinematics; Robot sensing systems; Robot vision systems; Sonar;
Conference_Titel :
Mechatronics and Automation, 2005 IEEE International Conference
Conference_Location :
Niagara Falls, Ont., Canada
Print_ISBN :
0-7803-9044-X
DOI :
10.1109/ICMA.2005.1626716
