ROBOT NAVIGATION IN VERY COMPLEX, DENSE, AND CLUTTERED INDOOR/OUTDOOR ENVIRONMENTS
Javier Mínguez Luis Montano
Computer Science and Systems Engineering, CPS, University of Zaragoza, Spain

This paper addresses the reactive collision free motion generation for indoor-outdoor robots which have geometric, kinematic, and dynamic constraints. Most of the current mobile robots are designed exhibiting some of these constraints: (1) typically they are circular, square, or rectangular robots and (2) they are differential driven robots, car like robots, tricycle robots, etc. On the other hand, many navigation methods do not take into account the specific shape or robots kinematics and dynamics. In this case, these methods relax some constraints or they rely on approximations. It is clear that this is a gap in research that needs to be closed, by devising mechanisms to generalize navigation methods to be applied over a wide range of mobile platforms. This paper focuses on the generalization of a reactive method, the Nearness Diagram Navigation, to work over a fleet of geometric, kinematic, and dynamic constrained indoor-outdoor mobile robots. This framework has been extensively tested using four indoor and one outdoor robots equipped with different sensors. To validate the method, we report experiments in unknown, non predictable, unstructured, cluttered, dense and complex environments.
Keywords: Autonomous mobile robots, obstacle avoidance, robot navigation
Session slot T-Tu-A05: Intelligent Autonomous Vehicles I/Area code 8f : Intelligent Autonomous Vehicles

|