Multimodal Object Detection using an Autonomous Mobile Robot

D. Di Paola, C. Marotta, A. Milella, G. Circirelli, and A. Distante (Italy)


Surveillance robotics, object detection, computer vision, laser data segmentation


This paper presents a novel multimodal approach for indoor environment monitoring by a mobile robot. The proposed system consists of a vision-based and a laser based module that match independently the current scene with a stored one, looking for new or removed objects. The matching process, in both modules, uses clustering on local data to detect point clouds. A fuzzy logic inference system is then implemented to evaluate environment changes and decide whether a significant variation of the scene has occurred. Results from experimental tests demonstrate the feasibility of the proposed method in robot surveillance applications.

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