MATEC Web Conf.
Volume 95, 20172016 the 3rd International Conference on Mechatronics and Mechanical Engineering (ICMME 2016)
|Number of page(s)||5|
|Section||Robot Design and Control|
|Published online||09 February 2017|
Dynamic Obstacle Detection Based on Background Compensation in Robot’s Movement Space
1 School of Mechanical Science and Engineering, Jilin University, Changchun City, Jilin Province, China, 130022
2 Master Degree Candidate, School of Mechanical Science and Engineering, Jilin University, Changchun City, Jilin Province, China, 130022
In the safety area of industrial production, robots are required to have the ability of quickly detecting the dynamic obstacles which appear in the working space of robots when robots move along a predefined route. In order to solve the problem of dynamic obstacles detection more effectively, the paper proposes a quick detection method based on background compensation for dynamic obstacles in robot movement space, which makes extraction of feature points on dynamic obstacles in robot movement space, establishes the background model of optical flow velocity field between adjacent frames and makes background compensation for images with the use of block-matching algorithm in order to realize quick and accurate dynamic obstacles detection in dynamic environment. The experiment results show that the obstacles detection method can effectively eliminate the background movement caused by the movement of camera at the end of robot and can extract a more complete target object. Moreover, it also has good robustness.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.