Autonomous Robot Navigation in Unknown Terrains: Incidental Learning and Environmental Exploration

The navigation of autonomous mobile machines, which are referred to as robots, through unknown terrains, i.e., terrains whose models are not a priori known is considered. We deal with point-sized robots in two-and three-dimensional terrains and circular robots in two-dimensional terrains. The two-dimensional (three-dimensional) terrains are finite-sized and populated by an unknown, but, finite, number of simple polygonal (polyhedral) obstacles. The robot is equipped with a sensor system that detects all vertices and edges that are visible from its present location. In this context, the work deals with two basic navigational problems. In the visit problem, the robot is required to visit a sequence of destination points, in a specified order, using the sensor system. In the terrain model acquisition problem, the robot is required to acquire the complete model of the terrain by exploring the terrain with the sensor. A framework that yields solutions to both the visit problem and the terrain model acquisition problem using a single approach is presented. The approach consists of incrementally constructing, in an algorithmic manner, an appropriate geometric graph structure (1-skeleton), called the navigational course. A point robot employs the restricted visibility graph and the visibility graph as the navigational course in two-and three-dimensional cases respectively. A circular robot employs the modified visibility graph. The algorithms to solve the visit problem and the terrain model acquisition problem based on the abovementioned structures are presented and analyzed.