|Título||Evaluation of Three Vision-Based Object Perception Methods for a Mobile Robotic Platform|
|Publication Type||Journal Article|
|Year of Publication||2012|
|Authors||Ramisa A, Aldavert D, Vasudevan S, Toledo R, de Mántaras RLópez|
|Journal||Journal of Intelligent and Robotic Systems|
This paper addresses object perception applied to mobile robotics. Being able to perceive semantically meaningful objects in unstructured environments is a ke capability in order to make robots suitable to perform high-level tasks in home environments. However, finding a solution for this task is daunting: it requires the ability to handle the variability in image formation in a moving camera with tight time constraints. The paper brings to attention some of the issues with applying three state of the art object recognition and detection methods in a mobile robotics scenario, and proposes methods to deal with windowing/segmentation. Thus, this work aims at evaluating the state-of-the-art in object perception in an attempt to develop a lightweight solution for mobile robotics use/research in typical indoor settings.
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