Integrating Linguistic Descriptions and Sensor Observations for the Navigation of Autonomous Robots

  • Jorge Gasós
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 61)


One of the main problems for autonomous robot navigation in unknown indoor environments is the difficulty identifying the objects in the robot’s working area from raw sensor observations. Range sensors (i.e., laser and ultrasonic sensors), the most commonly used type of sensors in mobile robot applications, only provide information about the existence of objects in some given positions of the space. A number of approaches [2,17,20,24] have shown that this information is enough to successfully perform obstacle avoidance even in cluttered environments. However, there are many applications that also require to identify the type of objects that have been detected in order that the robot can take appropriate decisions and operate on the environment. The transition from range data to object identification is a very difficult problem, particularly when no a priori environment knowledge is available.


Mobile Robot Linguistic Term Robot Navigation Ultrasonic Sensor Dead Reckoning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2001

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  • Jorge Gasós

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