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SAM: Sensory actuatory map for autonomous robots

SAM: The Sensory-Actuatory Map for autonomous robots, is an alternative approach to build topological maps. SAM is based on the Systemic Architecture approach of the SIGNAL project (IST-2000-29225,

SAM is a mapping method, which is based on the combination of topologically connected sensory and action information. This map has been realised within the SIGNAL project for an autonomous robot, and has been successfully evaluated using the real six wheeled autonomous robot within a testing environment. The proposed sensory-actuatory map (SAM) represents the environment by linking successive sensory items (SI) together using those actions (A) that lead to the respective (SI) sequence. This interconnection graph contains the topology of the environment in a way that can be used for planning and navigation.

The sensory information is acquired while the robot is moving through the world to be mapped. Thus, the robot gains experience and information about the environment. Within the stream of sensory information, the algorithm identifies self-contained fractions of it as special Sensory Items (SI). These sensory items should stand for the real world items to be mapped. They must be easy to recognise and
clearly distinguishable from each other.

The action commands (A) are the result of the robot controller that is guiding the robot trough the environment. A wall-following algorithm (for example) is well suited for this task, but other control algorithms that provide reproducible movements apply as well.

SAM implements the following properties:
- It must contain and represent spatial knowledge: e.g. distances, interconnections,
- It must contain information about special items: e.g. real world objects, metric positions, landmarks,
-It must associate the spatial knowledge with these items, and vice versa.
- It must reflect the existing topological properties between the items.
-It must be as specific as the mapped region is.
- The content of the map must be somehow accessible.
- The map must allow navigation tasks.
- There must be an algorithm to build the map.
- Map making must work, even if the circumstances are not ideal.

SAM is a widely useable approach to build maps, not only for autonomous robots, but as well for all other thinkable, active agents (web browsers, ...)

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Reported by

Div. of Neural Computation, University of Bonn
Roemerstr. 164
53117 Bonn
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