Automated valet parking services provide great potential to increase the attractiveness of electric vehicles by mitigating their two main current deficiencies: reduced driving ranges and prolonged refueling times. The European research project V-Charge aims at providing this service on designated parking lots using close-to-market sensors only. For this purpose the project developed a prototype capable of performing fully automated navigation in mixed traffic on designated parking lots and GPS-denied parking garages with cameras and ultrasonic sensors only. This paper summarizes the work of the project, comprising advances in network communication and parking space scheduling, multi-camera calibration, semantic mapping concepts, visual localization and motion planning. The project pushed visual localization, environment perception and automated parking to centimetre precision. The developed infrastructure-based camera calibration and semi-supervised semantic mapping concepts greatly reduce maintenance efforts. Results are presented from extensive month-long field tests.

Future requirements for drastic reduction of CO2production and energy consumption will lead to significant changes in the way we see mobility in the years to come. However, the automotive industry has identified significant barriers to the adoption of electric vehicles, including reduced driving range and greatly increased refueling times. Automated cars have the potential to reduce the environmental impact of driving, and increase the safety of motor vehicle travel. The current state-of-the-art in vehicle automation requires a suite of expensive sensors. While the cost of these sensors is decreasing, integrating them into electric cars will increase the price and represent another barrier to adoption. The V-Charge Project, funded by the European Commission, seeks to address these problems simultaneously by developing an electric automated car, outfitted with close-to-market sensors, which is able to automate valet parking and recharging for integration into a future transportation system. The final goal is the demonstration of a fully operational system including automated navigation and parking. This paper presents an overview of the V-Charge system, from the platform setup to the mapping, perception, and planning sub-systems.

In this paper, research towards a learning, cooperative robotic assistance is presented. The aim of this research is to develop a robot which can easily be instructed how to either perform task autonomously or in cooperation with humans. We describe the underlying representations and methods developed for teaching new tasks and environments. The functionality has been demonstrated in a number of factory and office settings. In this paper, an example from a service scenario in an office environment is presented.

In this paper we present a method for calculating optimal, collisionfree movements for nonholonomic mobile robots. This is formulated as a nonlinear optimal control problem and solved using advanced numerical methods. The concept of artifical potential fields is used for accounting for the obstacles in the environment. Apart from taking advantage of the large body of knowledge from the numerical methods community this has the virtue of facilitating a simple and general problem description. Experiments show that using this method, complex movements can be calculated in a timely fashion.