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The concept of a small 2-DOF camera-orientation system is presented and verified through prototype testing. This system is able to orient a camera around its pan and tilt axis with dynamics exceeding those of the human eyes. At the same time, the system is lightweight enough to be mounted on a human's head. These characteristics are very important, considering the application as part of a gaze-driven...
This paper describes a concept for the creation of a 3D model of the environment by a mobile robot. This technique is called SLAM-Simultaneous Localization and Mapping. In this case we use stereocamera to find the significant features by the SURF detector. The SURF detector will also serve for the matching of the correspondent points in the both images. These points will then be connected to the triangular...
We present a method for simultaneously locking on to a ground target and estimating the position of an unmanned aerial vehicle (UAV) under countermeasure (CM) conditions, where sensors are prevented from successfully tracking a target. Owing to the limited payload and power of the UAVs, we employ a monocular camera and a global positioning system (GPS) to carry out vision-based simultaneous localization...
We consider the problem of enabling a robot to autonomously open doors, including novel ones that the robot has not previously seen. Given the large variation in the appearances and locations of doors and door handles, this is a challenging perception and control problem; but this capability will significantly enlarge the range of environments that our robots can autonomously navigate through. In...
For successful deployment, personal robots must adapt to ever-changing indoor environments. While dealing with novel objects is a largely unsolved challenge in AI, it is easy for people. In this paper we present a framework for robot supervision through Amazon Mechanical Turk. Unlike traditional models of teleoperation, people provide semantic information about the world and subjective judgements...
Building knowledge for robots can be tedious, especially if focused on object class recognition in home environments where hundreds of everyday-objects - some with a huge intra class variability - can be found. Object recognition and especially object class recognition is a key capability in home-robotics. Achieving deployable results from state-of-the-art algorithms is not yet achievable when the...
In this paper we present a new system for a mobile robot to generate an articulated scene model by analyzing complex dynamic 3D scenes. The system extracts essential knowledge about the foreground, like moving persons, and the background, which consists of all visible static scene parts. In contrast to other 3D reconstruction approaches, we suggest to additionally distinguish between static parts,...
This paper describes a system for automatic mapping and generation of textured 3D models of indoor environments without user interaction. Our data acquisition system is based on a Segway RMP platform which allows us to automatically acquire large amounts of textured 3D scans in a short amount of time. The first data processing step is registration and mapping. We propose a probabilistic, non-rigid...
In this paper we will use stereo camera for 3D modeling of object in indoor environment. For mobile robot, navigation is a very important research area. Stereo vision can provide many information of the environment, and with these information robot can perform high level task. With our stereo vision system, firstly, we get disparity map from frames captured by the stereo camera. Then we extract the...
This paper presents a 3-second 3D reconstruction algorithm able to process a dense geometric approximation of the surrounding environment. Image acquisition is done by a stereoscopic panoramic system with two color catadioptric cameras mounted on a mobile robot. An algorithm running on a Graphical Processing Unit (GPU) processes the 3D reconstruction in real-time. As the camera system moves, new views...
To realize accurate recognition of human activities, many studies have been proposed using vision sensors. Vision sensors can reliably detect human in normal environment, but it is affected by sudden illumination changes and complex conditions, which are the major obstacles to the reliability and robustness of the system. To solve this problem, we proposed a novel integration method to combine bi-static...
In many mobile robotics applications involving exploration of unknown environments, it would be extremely useful to provide human operators with a real-time 3D visualization of the environment the robot is exploring. Although a great deal of progress has been made in the separate fields of photorealistic structure from motion and realtime vision-based robot localization and mapping (SLAM), the ultimate...
Our goal is that the robot learns specific objects (not object category) from images. The major problem here is how to separate the target object from the background. We create a scene model from an image sequence. The scene model contains both the target object and background. We separate the target object from the background by matching the scene model and training images having different backgrounds...
This paper present a method to acquire a realistic, visually convincing 3D model for indoor environment using a mobile robot platform with two laser range scanners and one omnidirectional camera. First, the vertical mounted laser scanner is used to acquire geometrical 3D model of indoor environment, while the horizontal mounted laser scanner is used to solve the simultaneous localization and mapping...
In this paper, we discuss a robot vision in order to perceive people and the environment around a mobile robot. We developed a tele-operated mobile robot with a pan-tilt mechanism composed of a camera and a laser range finder (LRF). In this paper, we propose a method for sensor fusion to extract a human from the measured data by integrating these outputs based on the concept of synthesis. Next, we...
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