Optimal landmark selection for triangulation of robot position

A mobile robot can identify its own position relative to a global environment model by using triangulation based on three landmarks in the environment. It is shown that this procedure may be very sensitive to noise depending on spatial landmark configuration, and relative position between robot and landmarks. A general analysis is presented which permits prediction of the uncertainty in the triangulated position.

In addition an algorithm is presented for automatic selection of optimal landmarks. This algorithm enables a robot to continuously base its position computation on the set of available landmarks, which provides the least noise sensitive position estimate. It is demonstrated that using this algorithm can result in more than one order of magnitude reduction in uncertainty.