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.


manipulators, object detection, robot vision.

Author keywords

object detection, grasping, robotics

Scientific reference

F. Rigual, A. Ramisa, G. Alenyà and C. Torras. Object detection methods for robot grasping: Experimental assessment and tuning, 15th Catalan Conference on Artificial Intelligence, 2012, Alacant, in Artificial Intelligence Research and Development, Vol 248 of Frontiers in Artificial Intelligence and Applications, pp. 123-132, 2012, IOS Press.