RAVON — The Robust Autonomous Vehicle for Off-road Navigation

With the aim of developing a vehicle that can fully autonomously operate in highly vegetated terrain, the University of Kaiserslautern’s Robotics Research Lab is conducting research in the field of off-road robotics. Their platform RAVON is a 4WD vehicle equipped with a large number of different sensor systems, which are used as basis for the hazard detection. RAVON’s navigation system is three-layered, consisting of a deliberative navigator on top of a behaviour-based pilot. The navigator’s job is to create and update topological maps of the robot’s environment, in which paths are calculated. The pilot tries to move the robot along such paths while keeping it away from obstacles. Collision avoidance is realised by a large number of behaviours that access the sensor data in a unified and straightforward way. An intermediate layer shall mediate between navigator and pilot and solve problems they cannot address properly. The purpose of this paper is to provide information about the platform RAVON and to present the concepts underlying the work in detail

Extension Approach for the Behaviour-Based Control System of the Outdoor Robot RAVON Autonome Mobile Systeme

Abstract. This paper describes the extension of a behaviour-based control system for autonomous outdoor navigation. To perform robust obstacle avoidance the existing stereo vision system is complemented with a 2D laser scanner. Instead of combining raw sensor data, the additional information is integrated exploiting behaviour fusion. The scanner data processing is wrapped into new behaviours, which are added to the existing network. That way no modifications to existing behaviours and interconnections are necessary. Furthermore sensors can be evaluated individually augmenting traceability and testability. The performance of the resulting system is shown in an experiment carried out on the outdoor robot RAVON.