This paper presents a 3D navigation subsystem providing specific treatments needed for the perception and the navigation of an all-terrain mobile robot. This subsystem was developed and integrated in the global framework of the EDEN experimentation. After a brief description of this outdoor navigation experimentation, we describe the natural environment representations we use. Two important perception functions based on 3D data are involved here: fast construction of elevation maps and robot localization. We then describe the 3D motion planner dedicated to the navigation on rugged terrains. The current state of integration of the experiment is finally presented by the mean of experimental results obtained from the natural environment of the mobile robot ADAM.>

The authors address the motion planning problem for wheeled vehicles moving on rough terrains. First, they formalize the placement problem for the case of a rather complex locomotion system consisting of n wheels attached to the robot body by passive suspensions. They next analyze the geometric and kinematic constraints acting on the placements of the robot. Finally, they present a planning method that computes a safe and feasible path between two given placements of the robot. The approach basically consists in searching a path into a graph built incrementally during the exploration of a discrete 3-D configuration space. The algorithms have been implemented, and simulation results are reported.

The authors address the motion planning problem for a robot and a movable object within polygonal obstacles. Motion planning in this context appears as a constrained instance of the coordinated motion planning problem for two robots. The object cannot move itself, it only does when the robot grasps it. A topological property that characterizes the existence of solutions in the subspace of configurations where the robot touches the object is discussed. This property provides a general resolution scheme which is applied to the special case of a convex polygonal robot moving in translation with a convex polygonal object amidst polygonal obstacles. The algorithm has been implemented, and experimental results are discussed.>