Model based active object localisation using multiple sensors

Describes an implementation of a model based multi-sensor localisation system using high frequency ultrasonic and selective infrared transducers. The sensor system is mounted on the end of an ADEPT robot arm and measurements are taken while the robot arm follows a pre-determined trajectory. The methodology is continuous estimation by tracking through prediction and observation. A sensor model and partial knowledge of the environment geometry is essential. The extended Kalman filter algorithm is used to recursively estimate the location of certain objects relative to the robot arm and the uncertainty of measurements and estimation process are also maintained. Optimal sensing strategies consisting of straight line motions are proposed based on effectiveness of uncertainty reduction. An implementation of the system as a hole finder for automatic freight container handling is investigated. Experimental results are presented together with simulated data. Utilisation of geometric constraints in localisation and estimation is discussed