Browsing by Subject "Robot vision"
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Item Building safety maps using vision for safe local mobile robot navigation(2009-08) Murarka, Aniket; Kuipers, BenjaminIn this work we focus on building local maps to enable wheeled mobile robots to navigate safely and autonomously in urban environments. Urban environments present a variety of hazards that mobile robots have to detect and represent in their maps to navigate safely. Examples of hazards include obstacles such as furniture, drop-offs such as at downward stairs, and inclined surfaces such as wheelchair ramps. We address two shortcomings perceived in the literature on mapping. The first is the extensive use of expensive laser-based sensors for mapping, and the second is the focus on only detecting obstacles when clearly other hazards such as drop-offs need to be detected to ensure safety. Therefore, in this work we develop algorithms for building maps using only relatively inexpensive stereo cameras, that allow safe local navigation by detecting and modeling hazards such as overhangs, drop-offs, and ramps in addition to static obstacles. The hazards are represented using 2D annotated grid maps called local safety maps. Each cell in the map is annotated with one of several labels: Level, Inclined, Non-ground, or, Unknown. Level cells are safe for travel whereas Inclined cells require caution. Non-ground cells are unsafe for travel and represent obstacles, overhangs, or regions lower than safe ground. Level and Inclined cells can be further annotated as being Drop-off Edges. The process of building safety maps consists of three main steps: (i) computing a stereo depth map; (ii) building a 3D model using the stereo depths; and, (iii) analyzing the 3D model for safety to construct the safety map. We make significant contributions to each of the three steps: we develop global stereo methods for computing disparity maps that use edge and color information; we introduce a probabilistic data association method for building 3D models using stereo range points; and we devise a novel method for segmenting and fitting planes to 3D models allowing for a precise safety analysis. In addition, we also develop a stand-alone method for detecting drop-offs in front of the robot that uses motion and occlusion cues and only relies on monocular images. We introduce an evaluation framework for evaluating (and comparing) our algorithms on real world data sets, collected by driving a robot in various environments. Accuracy is measured by comparing the constructed safety maps against ground truth safety maps and computing error rates. The ground truth maps are obtained by manually annotating maps built using laser data. As part of the framework we also estimate latencies introduced by our algorithms and the accuracy of the plane fitting process. We believe this framework can be used for comparing the performance of a variety of vision-based mapping systems and for this purpose we make our datasets, ground truth maps, and evaluation code publicly available. We also implement a real-time version of one of the safety map algorithms on a wheelchair robot and demonstrate it working in various environments. The constructed safety maps allow safe local motion planning and also support the extraction of local topological structures that can be used to build global maps.Item The effects of display format and visual enhancement cues on performance of three-dimensional teleoperational tasks(Texas Tech University, 1998-05) Park, Sung HaDepth perception (as a third dimension) on a two-dimensional surface of a display interface very much determines the quality of the teleoperation system. In this research, among various teleoperation sensing requirements, the television depth requirement was investigated in detail. This research was intended to extend our understanding of the effects of visual display formats and visual enhancement cues on the ability of human operators to effectively control robot manipulators in three-dimensions. Visual display formats and visual enhancement cues were evaluated by employing a pick-and-place (picking up a virtual object and placing it into a storage rack) task in a simulated teleorobotic task environment. Three different display formats, a multiple 2-dimensional (2-D) display, a 3-dimensional (3-D) perspective display, and a 3-D stereoscopic display were simulated using a combination of various programming tools (external motif, C language, and TELEGRIP software) on a SiliconGraphics Indigo2 workstation. In order to aid human operators in perceiving depth, four different visual enhancement depth cues (including no enhancement cue) were also proposed and incorporated into each display format. Task difficulties were generated by manipulating the size of the storage rack. To compare different display formats and visual enhancement cues, various teleoperation performance measures were collected under each display condition. The measures included the time-to-completion, accuracy, subjective ratings of workload, and distance (move by the end effector). The results showed that the multiple 2-D display was superior to the perspective and stereoscopic displays, if no visual enhancement cues were provided. If provided with two of the proposed visual enhancement cues, the translucent reference cylinder and four reference lines, the stereoscopic and perspective displays were equivalent to the multiple 2-D display. The traditional single reference line was not sufficient to provide appropriate depth information on the stereoscopic and perspective displays. The stereoscopic display resulted in better performance than the perspective display only under the high task difficulty condition.