3D scene modelling and curve-based localization in natural environments

Deals with perception functions required in an autonomous robot which must move in unknown natural environments. From a sequence of range images acquired during the motion, the robot must incrementally build a model and correct its situation estimate. This approach is suitable for environments in which (1) the terrain is mostly flat and (2) obstacles can be distinguished from the ground. The model gives ground and obstacle representations. In previous works, some obstacles emerging from the ground were selected as landmarks; in this paper, we present a new method: the boundary lines between the ground and the obstacles, can be approximated by B-spline curves so that stable curvature information can be extracted. The robot localization is performed from matchings between these curves perceived from different positions and from the numerical fusion between their models. Several experiments on actual images acquired in a lunar-like environment, are presented and analyzed.