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Visual Orientation and Motion Control of MAKRO – Adaptation to the Sewer Environment

Marina Kolesnik, Hermann Streich

发表年份
2002
引用次数
25

摘要

Adaptation has become an important aspect of robot design. The work here describes the perception and motion control of MAKRO- an autonomous robot for sewer inspection- from the point of view of MAKRO’s adaptation to specific features of the sewer environment. Two features are crucial for MAKRO’s adaptation. First, narrow sewer pipes connected into a unified system via junctions, compose a graph-like structure with rather constraint surface geometry. Second, a sewer interior is absolutely dark. The visual sensing of MAKRO is not only well adapted to these specific conditions, in fact it benefits from them. Visual orientation by a hybrid vision system gives rise to a rather simple vision model, which is capable of supporting real time orientation in the sewer. This instantiates an important principle of embodied cognition, which states that adaptation of an agent to an environment allows the use of simple principles of “cheap vision” for navigation purposes. Moreover, a fast visual processing enables MAKRO to react rapidly to events in its surroundings. This in turn, changes our approach to movement control: MAKRO does not act in the “plan – move ” fashion; instead, it explores the environment, updates its heading and finds the right direction for the next move in real time. This leads to a second principle of the current work: if visual orientation of an agent operates in real time, all that is required for its successful navigation is to continuously update the right direction of motion. Navigation of MAKRO gives a powerful demonstration of how adaptation to an ecological niche and the exploitation of environmental constraints can lead to extraordinarily robust performance in a mobile robot. 1.

关键词

Adaptation (eye)Computer scienceOrientation (vector space)RobotWork (physics)Constraint (computer-aided design)Visual processingPerceptionArtificial intelligenceHuman–computer interaction

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