Active Visual Object Search Using Affordance-Map in Real World : A Human-Centric Approach

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Conference Proceeding
Proceedings of the 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV), 2014, pp. 1427 - 1432
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Human context is the most natural explanation why objects are placed and arranged in a particular order in an indoor environment. Usually, humans arrange objects in order to support their intended activities in a given environment. However, most of the common approaches for robotic object search involve modelling object-object relationships. In this paper, we hypothesize such relationships are centered around humans and bring human context to object search by modelling human-objects relationships through affordance-map. It identifies locations in a 3D map which support a particular affordance using virtual human models. Therefore, our approach does not require to observe real humans in the scene. The affordance-map and object-human-robot relationship are then used to infer the object search strategy. We tested our algorithm using a mobile robot that actively searched for the object “computer monitors” in an office environment with promising results
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