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The ability to detect and follow a specific person is a key prerequisite of service mobile robots in indoor environments. A novel method for tracking and following a specific person with a mobile robot by combining vision and laser range information is proposed. The vision module which integrates the color matching method using the Horizontal-Projecting Probability Histogram (HPPH) of upper body color...
A probabilistic approach is proposed for Simultaneous robot Localization and Person-Tracking using Rao-Blackwellised particle filters (RBPF). Such filters represent posteriors over the person location by a mixture of Kalman Filters, where each is conditioned on a sample of robot pose. Furthermore, information collected via multi-modal sensors is utilized in the RBPFs framework to improve the performance...
People tracking and localization in situations with coexisting service robots is a challenging task due to the non-rigid nature of human body, complex background and frequent occlusions among people and robots. A multi-view approach is proposed to people-tracking and localization whilst the robotpsilas capability of perceiving environment is utilized. Initiated by person detection, tracking within...
The ability to detect and follow a specific person is considered to be a key prerequisite of service mobile robots in indoor environments. A novel vision-based tracking and following method for a mobile robot is proposed, which combines the clothes color features of the person's upper body and the contour of the head-shoulder. Horizontal-Projecting Probability Histogram (HPPH) of torso based on particular...
Perceiving the position of the mobile robot in an environment is an important element for an autonomous or semi-autonomous robot. In this paper we present a novel localization paradigm using topological map with tiered features, which is robust to rotation, illumination variations and scale changes. The topological model is extracted from natural landmarks and the normalized Zernike moments are calculated...
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