Jörg Langwald

Flexible robot-assembly using a multi-sensory approach

Recent research in industrial robotics aims at the involvement of additional sensory devices to improve robustness, flexibility and performance of common robot applications. Many different sensors have been developed over the past years to fit the requirements of different but very specific tasks. Special seam tracking sensors support the robot in welding applications. Vision systems are common in quality control and inspection. Force/torque sensors mounted to a robots wrist are still an exception and limited to the fields of scientific research. Compared to the number of annual robot sales the number of sensor equipped robots is still negligible, although the benefits of sensory feedback are obvious. In this paper we introduce a general approach to tackle the problem of sensor-based robot assembly. We realized a flexible assembly cell that includes a variety of different sensors for mating with moving parts.

The 3D-Modeller: A Multi-Purpose Vision Platform

This paper deals with the concept and implementation of a multi-purpose vision platform. In robotics, numerous applications require perception. A multi-purpose vision platform suited for object recognition, cultural heritage preservation and visual servoing at the same time is missing. In this work, we draw attention to the design principles for such a vision platform. We present its implementation, the 3D-modeller. In specifying and combining multiple sensors, laser-range scanner, laser-stripe profiler and stereo vision, we derive the required mechanical and electrical hardware design. The concepts for synchronization and communication round offs our approach. Precision and frame rate are presented. We illustrate the versatility of the 3D-modeller by addressing four applications: 3D-modeling, exploration, tracking and object recognition. Due to its low weight and generic mechanical interface, it can be mounted on industrial robots, humanoids, or free-handed as well. The 3D-modeller is flexibly applicable, not only in research but also in industry, especially in small batch assembly.

FPGA based real-time visual servoing

Real-time image processing tasks not only require high computing power but also high data bandwidth. Though current processors excel in computing power, memory throughput is still the bottleneck for stream-oriented applications such as low-level image processing tasks. The alternative of special-purpose systems lacks flexibility at a high design effort and long development time. This effort often becomes void by the rapid advance of mainstream computing technology. FPGA technology promises flexibility and the necessary computing performance at affordable design costs. In this paper, we describe our approach for a prototype image processing system for robot vision applications, based on FPGA technology. We use a commercially available PCl-board to implement a typical application based on the experimental servicing satellite (ESS) scenario.

Robuste Echtzeitverfolgung kreisförmiger Objektmerkmale mittels Hough-Transformation

Die Hough-Transformation ist ein robustes Verfahren zur Extraktion verschiedenster geometrischer Merkmale aus Bilddaten. Der sehr hohe Rechenzeit- und Speicheraufwand verhindert aber im allgemeinen den Einsatz in Echtzeitanwendungen. In diesem Beitrag wird die Implementierung einer Hough-Transformation vorgestellt, die es ermoglicht, kreisformige Strukturen in Videoechtzeit zu verfolgen. Bei unmittelbarer Anwendung des allgemeinen Ansatzes der Hough-Transformation ergeben sich dabei erhebliche Diskretisierungsprobleme, die berucksichtigt werden mussen. Der erreichte Verarbeitungstakt liegt bei 50 Hz bei einer Gesamttotzeit von 3 Takten. Das besprochene Verfahren wird in einem System zur modellgestutzten visuellen Lageregelung eines Roboterendeffektors eingesetzt.