Insects and a lot of other animals use the optical flow to control the direction of their motion and to avoid obstacles. This paper describes experiments suggesting the possible use of the optical flow for the navigation of a robot moving in indoor and outdoor environments. In indoor scenes, such as corridors, offices and laboratories, the optical flow is used to detect and localize obstacles. These routines are based on the computation of a reduced optical flow. Almost real time performance was obtained with standard workstations, such as SUN 3 or SUN Sparcstation 1. The mobile vehicle is usually able to avoid large obstacles such as a chair or a human, but it is not able to avoid thin obstacles such as a rod or a bar. The avoidance performances of the proposed algorithm critically depend on the feedback loop between the vision module and the motor system. In outdoor scenes the optical flow can be used to understand the egomotion, that is to obtain information on the absolute velocity of the moving vehicle. The optical flow is corrected for shocks and vibration present during image acquisition. Regions of the image are extracted, where the optical flow is reliable, and the information on egomotion is recovered from the optical flow here obtained. These results suggest that the optical flow can be successfully used by biological and artificial systems for controlling their motion and for avoiding obstacles.

A general procedure for the understanding of a class of indoor scenes is proposed. The suggested algorithm makes use of an extensive 2-D processing of the image that provides a faithful line drawing of the viewed scene. It also uses procedures adequate for the understanding of the 3-D structure and for the recognition of several items in the scene. The approach is specific for indoor scenes, such as corridors, offices, and laboratory rooms, where long straight edges are predominant and vanishing points can be detected.>

The main goals of Computer Vision are the recovery of the three dimensional structure and the recognition of viewed objects from T.V. images. The understanding of images of indoor scenes, such as corridors and offices, is greatly simplified by the exploration of geometrical properties of the viewed scene. In these scenes there are many long straight edges which are either parallel or orthogonal and the viewed objects can be modeled as elements of Legoland. Legoland is a block world where physical edges have at most three directions, which are mutually orthogonal. In this paper a general procedure is proposed for the understanding of indoor scenes which is likely to be useful in Computer Vision. The proposed algorithm makes use of an extensive 2D image processing which is able to provide a faithful line drawing of the viewed scene. It also uses procedures adequate for both the understanding of the 3D structure of the viewed scene and for the recognition of several items in the scene.