.png){kind=icon}
.png){kind=icon}
Return
Multi-View Camera Pose Estimation for Robotic Arm Manipulation
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2020.3026108.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This article proposes a novel approach aimed at estimating the pose of a camera, affixed to a robotic manipulator, against a target object. Our approach provides a way to exploit the redundancy of the robotic arm kinematics by directly considering manipulator poses in the model formulation for camera pose estimation. We adopt a single camera multi-shot technique that minimizes the reprojection error over all the rigid poses. The results of the proposed method are compared to four other studies employing either monocular or stereo setup. The experimental results on synthetic and real data show that the proposed monocular approach achieves better and in some cases comparable results to the stereo approach. Moreover, the proposed approach is significantly more robust and precise compared to other methods.
Keywords:
Cameras
Robot vision systems
Pose estimation
Robot kinematics
Manipulators
Service robots
Pose estimation
multi-view
multi-shot
machine vision
robotic arm
visual servoing
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.