DocumentCode
2772822
Title
Trajectory tracking control of the guiding and following mobile robots: Elliptic collision-Free approach
Author
Yu, Wen-Shyong ; Lin, Chih-Hao
Author_Institution
Dept. of Electr. Eng., Tatung Univ., Taipei, Taiwan
fYear
2012
fDate
10-15 June 2012
Firstpage
1
Lastpage
8
Abstract
In this paper, a trajectory tracking control strategy by elliptic collision-Free approach is proposed for guiding and following mobile robots. Each robot is setup with a single eye camera to capture the image of a guiding robot or obstacle. The image between them is converted to a gray form, and then to the gradient for each pixel of Gaussian pyramid level to estimate the motion parameters, disturbances, or obstacles. Successive images for a moving object are used to estimate or recognize the foreground, guiding robot, and obstacles by calculating the gravity of the moving object, and then the following mobile robot will follow the trajectory of the guiding one. On the contrary, the following mobile robot turns out to serve as a guiding one when there is no gravity. Furthermore, the elliptic collision-free path will be used for obstacle gravity and keep going until the final destination is achieved. Finally, experimental results will be used to show the effectiveness of the proposed method.
Keywords
Gaussian processes; cameras; collision avoidance; image recognition; mobile robots; motion estimation; object tracking; parameter estimation; robot vision; trajectory control; Gaussian pyramid level; disturbance estimation; elliptic collision-free path; eye camera; following mobile robots; foreground recognition; gradient image; gray image; guiding mobile robots; guiding robot image; guiding robot recognition; motion parameter estimation; obstacle estimation; obstacle gravity; obstacle image; obstacle recognition; trajectory tracking control; Collision avoidance; Gravity; Mobile robots; Robot kinematics; Trajectory; Wheels; elliptic collision-free approach; guiding and following mobile robots; obstacles; trajectory tracking control;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), The 2012 International Joint Conference on
Conference_Location
Brisbane, QLD
ISSN
2161-4393
Print_ISBN
978-1-4673-1488-6
Electronic_ISBN
2161-4393
Type
conf
DOI
10.1109/IJCNN.2012.6252564
Filename
6252564
Link To Document