Considering the current state in service-robotics, an expert is still necessary to add new tasks and execution behaviors by textual and error-prone programming. Under the consideration that humans typically execute same activities almost identical (or at least similar) and further combine simple behaviors to more complex activities, we follow the constitutive assumption that all complex behaviors are composed of a limited set of atomic behaviors. This work introduces a generic framework for spatial-temporal analysis and classification of arbitrary atomic behaviors. Therefore, we propose the combination of Self-Organizing Maps (SOM) and Probabilistic Graphical Models (PGM) in order to exploit the advantages of both concepts. In this work, we describe the essential methods of the framework briefly, whereas the data-driven training of the spatial-temporal model and the reasoning process are described in detail. In order to demonstrate the potential and to emphasize the high level of generalization and flexibility in real-world environments, the framework is evaluated in an exemplary scenario.

This paper presented an approach to create 3D object models for robotic and vision applications in a fast and inexpensive way compared to established approaches. By using the RoboEarth system for storing the created object models users have world-wide access to the data and can immediately reuse a model as soon as it was created and uploaded. The approach shows general applicability for different kinds of cameras. In this work this was shown by two example implementations for the recognition process of objects. The quality of the recognition can be verified in the video. Combined with the knowledge saved in the RoboEarth database the objects can also be properly classified.

Collective working allows microrobots to achieve more functionality, better performance and higher reliability on the macroscopic level. In this paper we demonstrate the on-going work in developing novel collective systems, where swarm robots work not only collectively, but are also capable of autonomous aggregation and disaggregation into a higher multi- robot organism. The main issues of such an organism, as well as its genome-based control, are discussed. We show the developed docking approach and investigate topological transformations in a prototype of self-assembling robots.

In this paper, a new algorithm for cooperative path planning in a multi-robot system is introduced. The algorithm is specially designed for a distributed system with a large number of robots, all of which should be able to reach their respective goal positions without blocking each other, even if the environment is heavily constricted by obstacles. The basic idea of the approach is based on fully distributed path planning without any central instance, but with the ability of communication and cooperation between the robots. Path planning is done on local sections of the time-space configuration space. Dynamic conflicts between the robots are solved by the heuristic adjustment of priority values. By a continuous enhancement of all plans the algorithm is very robust against dynamic changes and erroneous robot behavior

Every embedded real-time system is inevitably time-restricted. Therefore, worst-case execution times (WCETs) have to be known. The static timing analysis of embedded software promises the calculation of safe upper time bounds. We present the results of a case study which reveal the special challenges of this methodology in the automotive domain. For most of the encountered problems we describe our solutions or propose possible methods for a solution.

This work is primarily devoted to specific communication and sensing approaches applied for large microrobotic swarms. We investigate the minimal capabilities of a microrobot which still enable the whole robotic group to perform collective activities. These minimal capabilities are implemented in the hardware which allows exploring a phenomenon of swarm intelligence in real experiments. The components of the developed system consume energy provided by microcontroller's I/O ports, are cheap and available on micro-component market.

For many applications in the fields of robotics, satellite imagery and medical imaging demanding real-time solutions, recognizing the crucial parts or structures in the given images continues to attract more attention. Tims, the paramount factor in these computer vision related fields is matching the objects in the images. Often graphs are used to represent the objects. It is well-known that graph matching is NT-complete problem in general. To accomplish the need of real-time solutions, various lower order complexity algorithms are developed with specific conditions. Here, a novel Node Neighbour Isomorphism (NNI) is introduced which efficiently matches two graphs in O(n/sup 4/) where n is the number of vertices in both the graphs which can be weighted and attributed. Using tliis NNI, the vertices of the graphs are grouped mutually exclusively. Instead of matching all the vertices, only the relevant NNI vertices alone are matched paving way for ample efficiency by reducing the number of matching operations. The algorithm is implemented on Sun Ultra 10 and results of crucial examples and random graphs are also tabled. The run-time performance and novality of the algorithm exemplifies the efficiency of the algorithm which also exhibits parallelism. The algorithm is compared with standard methods and requires the minimal time for matching the graphs.

The paper explores a view-based approach to recognize free-form objects in range images. We are using a set of local features that are easy to calculate and robust to partial occlusions. By combining those features in a multidimensional histogram, we can obtain highly discriminant classifiers without the need for segmentation. Recognition is performed using either histogram matching or a probabilistic recognition algorithm. We compare the performance of both methods in the presence of occlusions and test the system on a database of almost 2000 full-sphere views of 30 free-form objects. The system achieves a recognition accuracy above 93% on ideal images, and of 89% with 20% occlusion.

Accurate and reliable localization is a base requirement for a mobile robot. Landmark localization is a very common technique to do this. The arrangement of landmarks is important for reliable and accurate estimation of localization data. In this paper the optimized arrangement of artificial landmarks is discussed and a solution for building an accurate and reliable localization system based on combining artificial and natural landmarks is presented. Landmark placement is done by definition and optimization of a confidence level describing the expected localization estimation error. Areas in the environment which are ill conditioned by natural landmarks are furnished with additional artificial landmarks. The proposed system has been tested in a simulation and with a mobile robot in a real office environment.

We present an approach of a distributed planning method to solve dynamically some typical tasks of a production planning system in a flexible manufacturing system (FMS) at control level without using a fixed central component during planning and execution of orders received by one or several production planning systems above the control level. To achieve this, a flexible manufacturing system has been modelled as a multi-agent system, while the planning method we present uses the structure of manufacturing plans to coordinate properly their activities through negotiation among the agents. This has been implemented and tested in an object-oriented simulation environment.>

This paper tries to solve three questions. The first question is which of the knowledge based planning techniques are to be used or must be developed further in order to provide autonomous robots with appropriate intelligence. The second question illustrates which planning modules has already been implemented under the light of new planning techniques. In the last theme the various concepts for control systems of autonomous vehicles are constructed.