Simultaneous localisation and map building for autonomous guided vehicles

As autonomous guided vehicles claim wider applications, the need for a flexible navigation system increases. Previously developed systems designed to incorporate localisation and environmental modelling have suffered from poor operation speed, often depending upon a “stop look update” policy. We describe a multi-track extended Kalman filter navigation system which offers real time localisation while simultaneously constructing a map consisting of geometric features, each in turn described by an extended Kalman filter. Dynamic operation is achieved by utilising the increased scan rate and data quality of infrared scanning to overcome the need for a multi-hypothesis framework or other such computationally expensive paradigm