Map generation from unknown planar motion using omni-directional vision

Abstract

Describes a method to construct a stationary environmental map and estimate the ego-motion of a mobile robot from unknown planar motion by using an omni-directional vision sensor. Most environments where a mobile robot works are limited to two-dimensional space and the environmental map which is necessary for mobile robot navigation has also two dimensions. However conventional "structure from motion (SFM)" algorithms cannot be applied to two-dimensional space in perspective projection. We propose a SFM algorithm that can be applied to two-dimensional space. The proposed SFM algorithm exploits the azimuths of features which are obtained from an omni-directional vision sensor and gives robust results against the noise of image information by taking advantage of the large field of view. A relation between observed azimuths and motion parameters of a robot are constrained by a nonlinear equation and our method obtains all the motion parameters and an environmental map through a two-step procedure of solving the equation.