A real-time system for the control of an autonomous vehicle consisting of a nested hierarchy of control modules is described. The focus is on the PILOT module which provdies the real-time guidance of the system. It is responsible for the generation and tracking of dynamically feasible trajectories which follow the generally planned path and avoid local obstacles. The PILOT operation is based on a combination of simple rules and heuristic search. The state space consists of two parts: the lower level state space which represents the model of the world as a set of relationships among the units of vehicle state variables representing steering, acceleration, and velocity, as well as positions of obstacles, and the upper level state space where the relationships among generalized objects are represented as rules. Rules provide simple elementary maneuvers, and are applied when the upper level situation is easily recognized. Otherwise the situations are handled by the lower level search. Example runs of the vehicle are simulated to demonstrate the complexity of behavior. The algorithm has also been tested on a gas powered dune buggy developed at Drexel University.

An algorithm NAVIGATOR for robot path planning in a 2D world with polygonal obstacles is presented. The method employs A* search in a subset of the visibility graph of obstacle vertices. A procedure is given for finding this subset of the visibility graph without computing line intersections. The NAVIGATOR module is part of a complete hierarchical system for control and world representation for a robot which operates in an unkown and unstructured environment.

In a 2-1/D world an isolines-based world representation is employed. An algorithm of navigation is proposed based upon polygonization of the isolines, and use of the vertices of the polygon as nodes in the graph search. Quanitative recommendations are given concerning the required density of isolines and the error of polygonization. When a physical model of mechanical motion is applied, this algorithm of navigation provides minimum-time trajectories of motion. The results of navigation are illustrated using a simulation system developed for an Intelligent Mobile Autonomous System (unmanned robot).