Cognitive Recognition Under Occlusion for Visually Guided Robotic Errand Service

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 302)


A reliable vision system for running robotic errand service in an unstructured indoor environment such as homes is difficult to construct. Many visual challenges, such as perspective, clutter, illumination, and occlusion, need to be handled appropriately. While most of previous researches addressed these problems from the contexts of either object recognition or object searching, our proposed approach relies on a solution that combines these two as one. We are proposing a “Cognitive Recognition” System. In the proposed cognitive recognition system, information gathered from scene recognition helps deciding the next optimal perspective, and environmental parameters measurements determine the uncertainty in recognition measurements and thus the proper probability map update used in object search. We show particularly in this paper how this approach provides a practical solution to cluttered and occluded environments. And we demonstrate the results with our HomeMate Service Robot.


Object recognition Evidence collection Object searching  Occlusion management Cluttered environment Illumination variation  Visually-guided service robot Errand service for elderly 



This work is supported in part by MEGA Science R&D Project, funded by Ministry of Science ICT and Future Planning (NRF-2013MIA3A3A02042335), in part by Technology Innovation Program (10048320) funded by Ministry of Trade, Industry and Energy, and in part by Basic Science Research Program through NRF (NRF-2010-0020210) funded by Ministry of Education.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.School of Information and Communication EngineeringSungkyunkwan UniversitySuwonSouth Korea

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