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A principal step towards solving diverse perception problems is segmentation. Many algorithms benefit from initially partitioning input point clouds into objects and their parts. In accordance with cognitive sciences, segmentation goal may be formulated as to split point clouds into locally smooth convex areas, enclosed by sharp concave boundaries. This goal is based on purely geometrical considerations and does not incorporate any constraints, or semantics, of the scene and objects being segmented, which makes it very general and widely applicable. In this work we perform geometrical segmentation of point cloud data according to the stated goal. The data is mapped onto a graph and the task of graph partitioning is considered. We formulate an objective function and derive a discrete optimization problem based on it. Finding the globally optimal solution is an NP-complete problem; in order to circumvent this, spectral methods are applied. Two algorithms that implement the divisive hierarchical clustering scheme are proposed. They derive graph partition by analyzing the eigenvectors obtained through spectral relaxation. The specifics of our application domain are used to automatically introduce cannot-link constraints in the clustering problem. The algorithms function in completely unsupervised manner and make no assumptions about shapes of objects and structures that they segment. Three publicly available datasets with cluttered real-world scenes and an abundance of box-like, cylindrical, and free-form objects are used to demonstrate convincing performance. Preliminary results of this thesis have been contributed to the International Conference on Autonomous Intelligent Systems (IAS-13).
Business process infrastructures like BPMS (Business Process Management Systems) and WfMS (Workflow Management Systems) traditionally focus on the automation of processes predefined at design time. This approach is well suited for routine tasks which are processed repeatedly and which are described by a predefined control flow. In contrast, knowledge-intensive work is more goal and data-driven and less control-flow oriented. Knowledge workers need the flexibility to decide dynamically at run-time and based on current context information on the best next process step to achieve a given goal. Obviously, in most practical scenarios, these decisions are complex and cannot be anticipated and modeled completely in a predefined process model. Therefore, adaptive and dynamic process management techniques are necessary to augment the control-flow oriented part of process management (which is still a need also for knowledge workers) with flexible, context-dependent, goaloriented support.
The objective of this research project is to develop a user-friendly and cost-effective interactive input device that allows intuitive and efficient manipulation of 3D objects (6 DoF) in virtual reality (VR) visualization environments with flat projections walls. During this project, it was planned to develop an extended version of a laser pointer with multiple laser beams arranged in specific patterns. Using stationary cameras observing projections of these patterns from behind the screens, it is planned to develop an algorithm for reconstruction of the emitter’s absolute position and orientation in space. Laser pointer concept is an intuitive way of interaction that would provide user with a familiar, mobile and efficient navigation though a 3D environment. In order to navigate in a 3D world, it is required to know the absolute position (x, y and z position) and orientation (roll, pitch and yaw angles) of the device, a total of 6 degrees of freedom (DoF). Ordinary laser-based pointers when captured on a flat surface with a video camera system and then processed, will only provide x and y coordinates effectively reducing available input to 2 DoF only. In order to overcome this problem, an additional set of multiple (invisible) laser pointers should be used in the pointing device. These laser pointers should be arranged in a way that the projection of their rays will form one fixed dot pattern when intersected with the flat surface of projection screens. Images of such a pattern will be captured via a real-time camera-based system and then processed using mathematical re-projection algorithms. This would allow the reconstruction of the full absolute 3D pose (6 DoF) of the input device. Additionally, multi-user or collaborative work should be supported by the system, would allow several users to interact with a virtual environment at the same time. Possibilities to port processing algorithms into embedded processors or FPGAs will be investigated during this project as well.
Ziel des hier beschriebenen Forschungsprojekts war die Entwicklung eines prototypischen Fahrradfahrsimulators für den Einsatz in der Verkehrserziehung und im Verkehrssicherheitstraining. Der entwickelte Prototyp soll möglichst universell für verschiedene Altersklassen und Applikationen einsetzbar sowie mobil sein.
Design of a declarative language for task-oriented grasping and tool-use with dextrous robotic hands
(2014)
Apparently simple manipulation tasks for a human such as transportation or tool use are challenging to replicate in an autonomous service robot. Nevertheless, dextrous manipulation is an important aspect for a robot in many daily tasks. While it is possible to manufacture special-purpose hands for one specific task in industrial settings, a generalpurpose service robot in households must have flexible hands which can adapt to many tasks. Intelligently using tools enables the robot to perform tasks more efficiently and even beyond the designed capabilities. In this work a declarative domain-specific language, called Grasp Domain Definition Language (GDDL), is presented that allows the specification of grasp planning problems independently of a specific grasp planner. This design goal resembles the idea of the Planning Domain Definition Language (PDDL). The specification of GDDL requires a detailed analysis of the research in grasping in order to identify best practices in different domains that contribute to a grasp. These domains describe for instance physical as well as semantic properties of objects and hands. Grasping always has a purpose which is captured in the task domain definition. It enables the robot to grasp an object in a taskdependent manner. Suitable representations in these domains have to be identified and formalized for which a domain-driven software engineering approach is applied. This kind of modeling allows the specification of constraints which guide the composition of domain entity specifications. The domain-driven approach fosters reuse of domain concepts while the constraints enable the validation of models already during design time. A proof of concept implementation of GDDL into the GraspIt! grasp planner is developed. Preliminary results of this thesis have been published and presented on the IEEE International Conference on Robotics and Automation (ICRA).
Vielfalt ist unser Angebot
(2014)
Der Fachbereich Sozialversicherung der Hochschule Bonn-Rhein-Sieg blickt auf zehn erfolgreiche Jahre zurück. Seit Gründung des Fachbereichs im Jahr 2003 arbeiten Wissenschaftlerinnen und Wissenschaftler verschiedener Disziplinen auf dem Campus Hennef eng vernetzt im Untersuchungsfeld der Sozialversicherung.