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This paper presents a vision-based obstacle avoidance design using a monocular camera onboard a mobile robot. An image processing procedure is developed to estimate distances between the robot and obstacles based-on inverse perspective transformation (IPT) in image plane. A robust image processing solution is proposed to detect and segment navigatable ground plane area within the camera view. The...
Many robotic vision systems suffer from unsatisfied recognition rate and high computational load. A solution to the design of a fast and sufficiently accurate robotic vision system requires urgent attention. This paper presents a novel image processing architecture for visual attention and tracking applications using a series of low-level image processing units. The proposed system features a human-mimic...
This paper presents an intruder detection system which consists of a Zigbee sensor network and an autonomous mobile robot. Multiple Zigbee sensor modules installed in the environment can detect intruders and abnormal conditions. Sensor nodes transmit intrusion alarm to the monitoring center as well as the mobile robot via Zigbee wireless mesh network. The robot can navigate in the environment autonomously...
This paper presents a novel method for mobile robot localization based on multi-robot cooperative sensing. A multi-robot cooperative localization scheme is proposed using visual detection and sensor data fusion. The visual detection system employs a stereo vision module for both observing other robots and obtaining environmental information. Each mobile robot is able to recognize its teammates by...
Human detection and tracking is important for user-friendly human-robot interaction. The robot should be able to find the user autonomously and keep its attention to the user in a human-like manner. In this paper, a design and experimental study of robust human detection and tracking is presented through fusion several modalities of sensory information. The multi-modal interaction design utilizes...
This paper presents a novel algorithm of image-based motion detection for lateral driving assistance. We propose a feature-based motion detection algorithm, which combines optical-flow estimation and road plane segmentation using FOE concept. The developed algorithm can segment moving objects from a changing background efficiently. Both cars and motorcycles on the lateral side of a driving vehicle...
This paper presents a design and implementation of a real-time visual tracking system for vehicle safety applications. A novel feature-based vehicle tracking algorithm is proposed. This algorithm can automatically detect and track multiple moving objects, including cars and motorcycles, ahead of the tracking vehicle. Combined with the concept of focus of expansion (FOE) and scene analysis, the developed...
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