Copyright © lFAC Intelligent Components for Vehicles, Seville, Spain, 1998 GUIDANCE OF AUTONOMOUS VEHICLES BY MEANS OF STRUCTURED LIGHT Jose Luis Lazaro Galilea, Alfredo Gardel Vicente, Manuel Mazo Quintas, Cesar Mataix G6mez, Juan Carlos Garcia Garcia, Departamento de Electronica. Universidad de AlcaM Campus Universitario sin. 28871 Alcala de H (Madrid). Tel.:34 1 8854810-13. Fax.: 34-1-8854804. E-mail: {lazaro. alfredo. mazo.mataix)@depeca.alcala.es Abstract: This paper describes a system comprising a CCD sensor coupled with an infra-red emitter so that the emission of structured light then captured in the sensor CCD (vision angle 90°) gives the 3-D co-ordinates of the light impact points. Working from the co-ordinate matrix supplied, surrounding obstacles and vacant areas can be detected. The environment through which the robot may move is generated considering its dimensions and orientation. A check is made in the latest environment update of whether any obstacles balk the objective. If so, the path is varied so that the obstacle is avoided and the path optimum. Copyright © 1998 IFAC Keywords: Obstacle detection, Robot navigation, Telemetry, Trajectory planning. 1. INTRODUCTION One technique for modelling an unknown environment in which a mobile robot is to be guided, involves obtai- ning 3D co-ordinates by emitting structured light and capturing it in a CCD camera (Jarvis 83). Beforehand, the whole system (camera and emitted light analyser) has to be jointly calibrated with reference to the same co-ordinates origin. If the structured light emitted consists of light planes, a co-ordinate can be deduced from each pixel resulting from the impact of said planes in the environment. The obtaining of so many co-ordinates allows a precise recognition of the presence of objects or limits of the physical environment. A deduction can therefore be made of the position of objects balking the robot's movement and the vacant spaces, so that the robot may move through the space without collisions. Related jobs making use of techniques to determine the object position and orientation can be found in (Blais et aI., 1988; Sato and Otsuki 1993; Kemmotsu and Kanade 1995). These papers have been developed with small depths and homogeneous background images. Motyl et 113 a1. (1993) and Khadroui et a1. (1995) have made use of these techniques for positioning a robot arm in an environment with an a-priori knowledge of objects such as polygonal and spherical ones. Evans et aI., (1990) and King (1990) have pointed out the use of structured light plane to detect the obstacles encounte- red by a mobile (MOB). The distance maps obtained may be used to deduce vacant, occupied and safety zones, generating paths that are updated according to the characteristics of the captured field of view. From the many path options, that should be chosen which gives some guarantee of safety while also observing the path to be followed. This paper achieves paths that are based on cubic- spline curves. Latombe (1993) have developed a navi- gation algorithm in order to obtain the space configura- tion in the surrounding environment. Koch (1985), (Oommen (1887) and Krogh and Feng (1989) shows some path planning algorithms to reach out the goal point. Payton (1986); Nitao and Parodi (1986); Brooks (1986) works with dynamic trajectories recalculated only when the surrounding environment changes.