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Proceedings Paper

Feature-level data fusion of a robotic multisensor gripper using ANN
Author(s): Ke-Jun Xu; Li-Biao Tong; Tao Mei
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Paper Abstract

Several kinds of sensors are installed in the robotic gripper. According to the outputs of multi-sensor, a data fusion technique is utilized to ensure the robot walking or grasping objects safely and reliably. In this paper, sensors of the gripper are introduced, such as force sensor for contact sensing and gripping force control, proximity sensor for collision prevention and position detection, and a displacement sensor for gripper openness control. The experiments of grasping objects with the gripper are presented, including firm grasp, virtual grasp, skew grasp, empty grasp and so on. The accurate information of grasping objects with the gripper is obtained using the multi-sensor data fusion technique based on the BP artificial neural network.

Paper Details

Date Published: 14 September 2001
PDF: 4 pages
Proc. SPIE 4414, International Conference on Sensor Technology (ISTC 2001), (14 September 2001); doi: 10.1117/12.440214
Show Author Affiliations
Ke-Jun Xu, Institute of Intelligent Machines and Hefei Univ. of Technology (China)
Li-Biao Tong, Hefei Univ. of Technology (China)
Tao Mei, Institute of Intelligent Machines (China)


Published in SPIE Proceedings Vol. 4414:
International Conference on Sensor Technology (ISTC 2001)

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