Detection of Multiple People by a Mobile Robot in Dynamic Indoor Environments

Detection of multiple people is a key element for social robot design and it is a requirement for effective human-robot interaction. However, it is not an easy task, especially in complex real world scenarios that commonly involve unpredictable motion of people. This paper focuses on detecting multiple people with a mobile robot by fusing information from different sensors over time. The proposed approach applies a segmentation method that uses the distance to the objects to separate possible people from the background and a novel adaptive contour people model to obtain a probability of detecting people. A probabilistic skin model is also applied to the images and both evidences are merged and used over time with a Bayesian scheme to detect people. We present experimental results that demonstrate how the proposed method is able to detect people who is standing, sitting and leaning sideways using a mobile robot in cluttered real world scenarios.

• Type: Journal
• Year: 2010
• Where: IBERAMIA
• Authors: José Alberto Méndez-Polanco, Angélica Muñoz-Meléndez, Eduardo F. Morales-Manzanares
• Keywords: Artificial Intelligence, IBERAMIA 2010, Mobile Robot, Multiple People, Real World Scenarios