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This paper proposes a new localization method for mobile robots based on received signal strength (RSS) in indoor wireless local area networks (WLANs). In indoor wireless networks, propagation conditions are very difficult to predict due to interference, reflection, and fading effects. As a result, an explicit measurement equation is not available. In this paper, an observation likelihood model is...
In this work, we present a multiple classifiers system cascades an on-line learning RGB-D appearance model framework in which detection, recognition, and tracking are highly coupled for a wheelchair robot equipped with a Kinect sensor to improve the efficiency of the care assistance and quality of accompanying service. The on-line trained classifiers use the surrounding background as negative examples...
In this paper, we present an approach to visual SLAM and human tracking for a wheelchair robot equipped with a Microsoft Kinect sensor that which is a novel sensing system that captures RGB and depth (RGB-D) images simultaneously. The speeded-up robust feature (SURF) algorithm is employed to provide the robust description of feature for environments and the target person from RGB images. Based on...
Human-robot interaction is an important issue for service robots. In this paper, we propose to utilize the multisensory data fusion to autonomously detect and track an accompanist as a target person in the surroundings of the mobile robot. First, we use laser range finder to detect the target person features which is characterized using distances and orientations from range sensor readings. Based...
Based on wireless local area networks (WLAN), this paper presents the navigation of a robotic wheelchair. We propose a radio based robot localization with a particle filter by using received signal strength from WLAN. An intelligent strategy is proposed to select the informative WLAN signals and reduce the algorithm complexity. Furthermore, we introduce a graphic feature node extraction to explore...
This paper presents a real-time vision system for assisting driver during nighttime driving. The proposed system provides the following features: 1) effectively detection and tracking of oncoming and preceding vehicles based on image segmentation and pattern analysis techniques. 2) Robust and adaptive vehicle detection under various illuminated conditions at nighttime urban environments benefited...
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