A real time local path planner is designed and developed. It is based on a specific environment modelling with square grid tessellation. Because of different motion requirements to achieve a mission, several path planners are developed that do forward or reverse motions and manoeuvres. The motion planning problem is formulated as the problem of motion of a point in a reduced sub-set of the configuration space. The implementation use intensively cellular automaton paradigm to compute the different stages of the processing.>

Scanning systems of existing range finders are sequential. The understanding and analysis of static range images has spread in the scientific community. Such images are widely used in the fields of vision and robotics. However, it is not yet clear what a range finder sees and what it does not see at high velocities. Depending on the scanning system, obstacles may be missed, if the vehicle velocity is not well related to the acquisition rate. A Laser Range Finder Scanning System Simulator such as LRF3S helps to relate vehicle motion to the scanning mechanism. Simulations show the location of each scanned point on the scene at speeds defined on the trajectory. The authors believe that they help to understand dynamic range images and that they are a framework for the design of a range finder scanning system best adapted for an application.>