Bernd Kuhlenkoetter

Applicability of stereo high speed camera systems for robot dynamics analysis

Industrial robots are widely used in industrial area. Requirements for more accuracy and stable performance are raised in the applications. Especially when the robot executes machining task, the dynamic performance in the machining process has influence on the work piece quality. This article utilizes a high speed camera measuring system to analyze the robot motion for the sake of process improvement. Linear paths with different accelerations are programmed. The position distributions in 3D space are presented and the path linearity is discussed. In addition, the path velocity and acceleration are obtained. The differences of the running velocity to programmed velocity are given. Changes of the accelerations are also described. According to this application, Characteristics of the measuring system are introduced. Evaluation is made based on the experiment results.

Task planning for human robot interactive processes

One of the next steps in factory automation might not exclusively be an automation issue, but instead combining robot and human skills to further improve industrial work processes. For various reasons, there is still a low dissemination of hybrid work processes characterized by direct human robot interaction. For instance, it is very difficult to decide which manual work processes are eligible for a transformation to a human-robot interactive process. Thus, the research project MANUSERV delivers a tool to support this decision process. Here, the central concept is a task planning system capable of generating automated as well as hybrid human-robot solutions. Therefore, a structured description of manual work processes forms the input to the planning system. Subsequently, a simulation system verifies and evaluates the proposed solutions and generates the necessary information for a transformation of the planning results to a real application scenario.

Adaptive Robot Based Reworking System

Surface quality plays an important role for both components and products. Either are an exact form and a dimensional accuracy required to fulfil a certain function, e.g. in the case of turbine blades, or the visual impression of a surface must meet high demands, e.g. in sanitary fittings. In order to meet these high demands in material processing, processes such as grinding and polishing are often used (VDMA, 2000). Nowadays the processes of grinding and polishing are automised by industrial robots to release the operator and to grant an economical manufacturing. Presently known systems however face the problem that they can be adjusted to other part geometries and processing cycles only at high costs and therefore are used only in large batches (Schraft & Kaun, 1999). One reason are the workintensive and time-consuming programming and optimisation of the movement paths, and another is that the handling systems do not recognize the existing defects on the surface resulting from grinding and polishing. As a defect-related adaptation to the subsequent processing steps is not possible, the reprocessing of the surfaces is done manually. In this chapter a concept is presented which makes it possible to automatise the reworking of design surfaces of high-quality sanitary fittings with the help of industrial robots.

Digital Assessment of Anthropometric and Kinematic Parameters for the Individualization of Direct Human-Robot Collaborations

For the human-centered design of ergonomic work systems, usually population based anthropometric percentile data tables, e.g. ISO 7250 [1] are used. Due to the recent trend to complex individual and small-batch productions, there is an increasing product and process variability. Thus, the need of robots without separating devices that can work in direct interaction with humans increases (human-robot collaboration, HRC). This form of direct collaboration between humans and robots is a major challenge for a human-centered and safe workplace design. The development of sensor technology, data processing as well as the interconnectivity with collaborative robots generally enables a flexible adjustment of the robot’s trajectory to the human prerequisites. Yet, to enhance the individualization of direct human-robot collaborations a more detailed knowledge of the anthropometric and kinematic profile of the employee would be beneficial. Manual anthropometric and kinematic measurements are time consuming and expensive and therefore not suitable as a standard process. To overcome this issue, the presented research project focusses on the optimization of this process by using markerless motion capturing. The processing and possible use of the captured data will be shown by the example of a use case, where the human parameters are used for a virtual simulation and optimization of a HRC-workplace. Afterwards, a self-written software tool for the Microsoft Kinect v2 sensor is presented for the digital assessment of anthropometric and kinematic human parameters. In the actual case, the anthropometric parameters are captured from a static T-Pose. For the determination of the kinematic profile the employee successively performs pre-defined max range of motion movements for each joint and degree of freedom. The motions were designed in line with the neutral-zero method [2].The data is stored in a comma separated value file. For the use with other systems it is possible to export the values with calculated offsets to the standard T-Pose. Further, preliminary results of a validation study for the digital assessment of the anthropometric parameters will be presented. The main objective of the presented work with markerless motion capturing is to enhance the digital collection of individual anthropometric and kinematic data. In addition, the possibilities and constraints for the use of these digital assessed parameters for customizable HRC-workplace designs are observed