Introducing autonomous machines to construction areas can improve many of the occurring processes. Therefore, this paper deals with problems in the field of creating an autonomous bucket excavator. A novel behavior-based approach for motion control is presented which allows natural boom trajectories, achieves good environment disturbance compensation behavior, guarantees safety of the movements concerning human beings and structures, and keeps a high extensibility of the system for future improvements. Furthermore, a simulation of soil deals as the basis for safe tests of the excavator's behavior in a simulated dynamic environment.

In this paper a combined action/perception-oriented approach for behavior-based robot software design is proposed. Action-oriented in that context denotes that the requirements for sensor information are directly derived from the navigational tasks on the control level. Perception-oriented design on the other hand determines further supporting behaviors from the data available. Taking into account the diversity of sensors and perception algorithms on the one hand and the need for a thorough control methodology on the other, the authors introduce a generic concept for sensor data abstraction through virtual sensors. Virtual sensors are standardized data representations which offer a clear interface for behavior-based robot control systems. The design method presented accounts for both, flexibility on the sensor processing layer and consistent structures on the control layer supporting reusability, extensibility, and traceability. Results documenting the applicability to complex robotic systems are shown in a case study about the off-road platform RAVON.

This paper presents a laser-based obstacle detection facility for off-road robotics in vegetated terrain. In the context of this work the mobile off-road platform RAVON was equipped with a 3D laser scanner and accompanying evaluation routines working on individual vertical scans. Identified terrain characteristics are used to build up a local representation of the environment. Introducing the abstraction concept of virtual sensors the transparent integration of additional terrain information on the basis of standardized behavior modules can be achieved.

This paper presents a robust Kalman-based localization for outdoor vehicles. Outdoor vehicles require a fault-tolerant system that can manage temporary unavailable sensor measurements. The sensor system of the vehicle consists of odometry, inertial measurement unit (IMU) and differential global positioning system (DGPS) receiver. The system allows full 3D localization including position, attitude and velocities. Final experiments showed the localization and navigation capabilities of the outdoor robot RAVON

Many tasks examined for robotic application like rescue missions or humanitarian demining require a robotic vehicle to navigate in unstructured natural terrain. This paper introduces a motion control for a four-wheeled offroad vehicle trying to tackle the problems arising. These include rough ground, steep slopes, wheel slippage, skidding and others that are difficult to grasp with a physical model and often impossible to acquire with sensory equipment. Therefore, a more reactive approach is chosen using a behavior-based architecture. This way a certain generalization in unknown environment is expected. The resulting behavior network is described and experiments performed in a simulation environment as well as in real world are presented. Additionally the performance of the utilized vehicle in case of mechanical or electronic defects is examined in simulation.