Autonomous Generation of Complete 3D Object Models Using Next Best View Manipulation Planning
Recognizing and manipulating objects is an important task for mobile robots performing useful services in everyday environments. In this paper, we develop a system that enables a robot to grasp an object and to move it in front of its depth camera so as to build a 3D surface model of the object. We derive an information gain based variant of the next best view algorithm in order to determine how the manipulator should move the object in front of the camera. By considering occlusions caused by the robot manipulator, our technique also determines when and how the robot should re-grasp the object in order to build a complete model.
Michael Krainin Brian Curless Dieter Fox
University of Washington,Department of Computer Science & Engineering,Seattle,WA 98195
国际会议
2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
上海
英文
5031-5037
2011-05-09（万方平台首次上网日期，不代表论文的发表时间）