ULTRASONIC CLASSIFICATION AND LOCATION OF 3D ROOM FEATURES USING MAXIMUM-LIKELIHOOD-ESTIMATION .1.

Current mobile robot ultrasonic localisation techniques use sensor sys tems which rely on features in a horizontal plane. The implicit assump tion is that the room boundary on the horizontal plane is not obstruct ed by objects such as furniture. This assumption is often not realisti c and restricts the versatility and portability of these systems. The solution proposed in this paper is the provision of sensing flexibilit y to use other 3D room boundaries (e.g. ceiling-wall intersections) as 3D natural beacons. We propose a 3D ultrasonic sensor array that uses a Maximum Likelihood Estimator to match the echo arrival times to dif ferent object classes and to determine the location of the 3D target. This method does not require fast data acquisition or powerful computi ng. It has been implemented on a robot localisation application with t he Extended Kalman Filter. This paper is the first of two parts, and p resents theoretical results on target classification and minimum trans ducer requirements. The second part, in the next issue of Robotica, pr esents experimental results on the characterisation of the sensor and its application to robot localisation, and includes the references for the both papers.