Arıkan, OrhanBarshan, Billur2016-02-082016-02-081995http://hdl.handle.net/11693/27761Date of Conference: 5-9 August 1995Conference Name: IEEE/RSJ International Conference on Intelligent Robots and Systems: Human Robot Interaction and Cooperative Robots, IEEE 1995The performance of a commonly employed linear array of sonar sensors is assessed for point-obstacle localization intended for robotics applications. Two different methods of combining time-of-flight information from the sensors are described to estimate the range and azimuth of the obstacle: pairwise estimate method and the maximum likelihood estimator. The variances of the methods are compared to the Cramer-Rao Lower Bound, and their biases are investigated. Simulation studies indicate that in estimating range, both methods perform comparably; in estimating azimuth, maximum likelihood estimate is superior at a cost of extra computation. The results are useful for target localization in mobile robotics.EnglishCollision avoidanceComputational methodsComputer simulationMobile robotsMotion controlParameter estimationSensorsSonarCramer-Rao lower bound methodMaximum likelihood estimatorObstacle localizationPairwise estimate methodSonar sensorsSensor data fusionConference Paper10.1109/IROS.1995.526268