Sonar-Based Real-World Mapping and Navigation by ALBERTO ELFES Presenter Uday Rajanna.

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Presentation transcript:

Sonar-Based Real-World Mapping and Navigation by ALBERTO ELFES Presenter Uday Rajanna

Involves a sonar based mapping and navigation system developed for an autonomous mobile robot operating in unknown or unstructured environments. An active range finding device based on an ultrasonic range transducer to build two dimensional maps of the robots surroundings. Each sonar distance reading provides information concerning empty and occupied volumes in a cone in front of the sensor. These empty and occupied readings are interpreted as empty and occupied probability distribution functions Range measurements from multiple points of view taken from multiple sensors are integrated into the sonar map. These measurements are constantly updated with the previous map to produce new maps, thereby increasing accuracy of detected probabilities of empty and occupied volumes.

R -> range measurement returned by the sonar sensor ε -> maximum sonar measurement error ω -> sensor bandwidth Ω -> solid angle subtending the main lobe of the sensitivity function. S -> position of the sonar sensor δ -> distance from P to S θ -> angle between the main axis of the beam and P as seen from S Probably Empty Region -> p E Somewhere Occupied Region -> p O

Dolphin Architecture: Multiple axis of representation of sonar mapping information (a) The Abstraction Axis Probabilistic representation, Geometric Level, Symbolic Level (b) The Geographical Axis View, Local Map, Global Map (c) The Resolution Axis Sensor-level local map and generate progression of maps with increasingly less detail

Conclusions: A Sonar based mapping and navigation system that proves to be able to operate in unknown and unstructured environments. This method provides a way of explicitly describing unknown, empty, and occupied areas. This can be combined with other robust techniques to perform effective navigation. This method combines well with the Matching technique described in the paper to determine the robots estimate of its position and orientation and also as a way to detect landmarks.