OBJECT RECOGNITION USING TACTILE IMAGE ARRAY SENSORS.

Ren C. Luo; Wen-Hsiang Tsai

doi:10.1109/ROBOT.1986.1087595

OBJECT RECOGNITION USING TACTILE IMAGE ARRAY SENSORS.

Ren C. Luo^*, Wen-Hsiang Tsai

^*Corresponding author for this work

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Scopus citations

Abstract

The authors develop an object recognition system through the combination of 2-D tactile image array and visual sensors. A video camera is used to acquire a top view image of an object and two tactile sensing arrays mounted on a gripper are used to detect tactile information about the lateral surfaces of the object. 3-D reference object models are established as a decision tree, and recognition of unknown objects is accomplished through measuring and comparing input object features with those of the reference objects. The clustering process and recognition procedures are described. The recognition scheme has been implemented, and the resulting decision tree is presented.

Original language	English
Title of host publication	Unknown Host Publication Title
Publisher	IEEE
Pages	1248-1253
Number of pages	6
ISBN (Print)	0818606959
DOIs	https://doi.org/10.1109/ROBOT.1986.1087595
State	Published - 1 Jan 1986

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abstract = "The authors develop an object recognition system through the combination of 2-D tactile image array and visual sensors. A video camera is used to acquire a top view image of an object and two tactile sensing arrays mounted on a gripper are used to detect tactile information about the lateral surfaces of the object. 3-D reference object models are established as a decision tree, and recognition of unknown objects is accomplished through measuring and comparing input object features with those of the reference objects. The clustering process and recognition procedures are described. The recognition scheme has been implemented, and the resulting decision tree is presented.",

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AB - The authors develop an object recognition system through the combination of 2-D tactile image array and visual sensors. A video camera is used to acquire a top view image of an object and two tactile sensing arrays mounted on a gripper are used to detect tactile information about the lateral surfaces of the object. 3-D reference object models are established as a decision tree, and recognition of unknown objects is accomplished through measuring and comparing input object features with those of the reference objects. The clustering process and recognition procedures are described. The recognition scheme has been implemented, and the resulting decision tree is presented.

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OBJECT RECOGNITION USING TACTILE IMAGE ARRAY SENSORS.

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