Synthesis of indoor maps in presence of uncertainty (original) (raw)

A robotic system is presented, which is able to autonomously explore unengineered indoor environments, thereby synthesising maps suitable for planning and navigation purposes. Map recovery takes place through interaction between the robot and the world, in which either sensing and acting are a ected by uncertainty. Kalman ltering is applied to maintain position best estimates, which are then fused with data coming from the observation of landmarks. The proposed method has been implemented on a robot equipped with ultrasonic range nders, and tested in a fairly simple, real environment.