Object Recognition for Manipulation Tasks in Real Domestic Settings: A Comparative Study
نویسندگان
چکیده
The recognition of objects is a relevant ability in service robotics, especially in manipulation tasks. There are many different approaches to object recognition, but they have not been properly analyzed and compared by considering real conditions of manipulation tasks in domestic setups. The main goal of this paper is to analyze some popular object recognition methods and to compare their performance in realistic manipulation setups. Object recognition methods based on SIFT, SURF, VFH, OUR-CVFH and color histogram descriptors are considered in this study. The results of this comparison can be of interest for researchers working in the development of similar systems (e.g. RoboCup @home teams).
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