TY - JOUR
T1 - Robot manipulator self-identification for surrounding obstacle detection
AU - Wang, Xinyu
AU - Yang, Chenguang
AU - Ju, Zhaojie
AU - Ma, Hongbin
AU - Fu, Mengyin
N1 - Publisher Copyright:
© 2016, The Author(s).
PY - 2017/3/1
Y1 - 2017/3/1
N2 - Obstacle detection plays an important role for robot collision avoidance and motion planning. This paper focuses on the study of the collision prediction of a dual-arm robot based on a 3D point cloud. Firstly, a self-identification method is presented based on the over-segmentation approach and the forward kinematic model of the robot. Secondly, a simplified 3D model of the robot is generated using the segmented point cloud. Finally, a collision prediction algorithm is proposed to estimate the collision parameters in real-time. Experimental studies using the KinectⓇ sensor and the BaxterⓇ robot have been performed to demonstrate the performance of the proposed algorithms.
AB - Obstacle detection plays an important role for robot collision avoidance and motion planning. This paper focuses on the study of the collision prediction of a dual-arm robot based on a 3D point cloud. Firstly, a self-identification method is presented based on the over-segmentation approach and the forward kinematic model of the robot. Secondly, a simplified 3D model of the robot is generated using the segmented point cloud. Finally, a collision prediction algorithm is proposed to estimate the collision parameters in real-time. Experimental studies using the KinectⓇ sensor and the BaxterⓇ robot have been performed to demonstrate the performance of the proposed algorithms.
KW - Collision prediction
KW - Manipulator self-identification
KW - Point cloud
KW - Superpixel
UR - http://www.scopus.com/inward/record.url?scp=84957935211&partnerID=8YFLogxK
U2 - 10.1007/s11042-016-3275-8
DO - 10.1007/s11042-016-3275-8
M3 - Article
AN - SCOPUS:84957935211
SN - 1380-7501
VL - 76
SP - 6495
EP - 6520
JO - Multimedia Tools and Applications
JF - Multimedia Tools and Applications
IS - 5
ER -