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Object detection methods for robot grasping: Experimental assessment and tuning
Ferran Rigual, Arnau Ramisa, Guillem Alenya, Carme Torras
123 - 132
10.3233/978-1-61499-139-7-123
Frontiers in Artificial Intelligence and Applications
Volume 248: Artificial Intelligence Research and Development
Abstract

In this work we address the problem of object detection for the purpose of object manipulation in a service robotics scenario. Several implementations of state-of-the-art object detection methods were tested, and the one with the best performance was selected. During the evaluation, three main practical limitations of current methods were identified in relation with long-range object detection, grasping point detection and automatic learning of new objects; and practical solutions are proposed for the last two. Finally, the complete pipeline is evaluated in a real grasping experiment.

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