Paper
1 March 1990 Using Multiple Markers In Graph Exploration
Gregory Dudek, Michael Jenkin, Evangelos Milios, David Wilkes
Author Affiliations +
Proceedings Volume 1195, Mobile Robots IV; (1990) https://doi.org/10.1117/12.969871
Event: 1989 Symposium on Visual Communications, Image Processing, and Intelligent Robotics Systems, 1989, Philadelphia, PA, United States
Abstract
A fundamental problem in robotics is that of exploring an unknown environment. Most current approaches to exploration make use of a global distance metric that is used to relate past sensory experiences to local measurements. Rather than rely on such an assumption we consider the more general problem of exploration without a distance metric, as is typical of exploring using only visual information: we propose robot exploration as graph building. In earlier papers we have shown that it is not possible for a robot to successfully explore a metricless environment without aid, but that by augmenting the robot with a single marker (which can be put down or picked up at will) it is possible for a robot to map its environment[1]. In this paper we present the extension of our algorithm to the case of k markers, and comment on the resulting decrease in time for exploration. By defining a minimal model for the world and the sensory ability of the robot, we separate spatial reasoning from visual perception. In this paper we deal only with the spa-tial reasoning component of the exploration problem, and assume that visual perception can identify the marker and the edges incident on the current location.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gregory Dudek, Michael Jenkin, Evangelos Milios, and David Wilkes "Using Multiple Markers In Graph Exploration", Proc. SPIE 1195, Mobile Robots IV, (1 March 1990); https://doi.org/10.1117/12.969871
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Cited by 15 scholarly publications.
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KEYWORDS
Mobile robots

Sensors

Visualization

Associative arrays

Error analysis

Information visualization

Environmental sensing

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