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Segmenting Objects through an Autonomous Agnostic Exploration Conducted by a Robot

Léni K. Le Goff, Ghanim Mukhtar, Pierre-Henri Le Fur, Stéphane Doncieux

Year
2017
Citations
4

Abstract

Human's everyday environment is an open environment in which objects with new shapes, colors or textures frequently appear. Enabling robots to deal with such environments and to manipulate those objects raises a difficult challenge: how to recognize an object? How to distinguish it from the background? An approach is proposed here to allow the robot to find this segmentation on its own. It relies on an active exploration of the environment aimed at identifying features of things that move after a contact with robot's end-effector. The only assumption made is that objects of interest are solid objects that the robot can move. The proposed approach can thus be applied without modifications to a large range of environments, as shown by the experiments performed by the robot.

Keywords

RobotArtificial intelligenceComputer scienceComputer visionMarket segmentationObject (grammar)SegmentationAutonomous robotRobot end effectorHuman–computer interaction

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