Robot calibration and modelling measurements are commonly performed using a laser tracker. To capture three-dimensional positions, a SMR is attached to the robot. While some researchers employ adhesive bonds for this purpose, such methods often result in inaccurate, unstable and non-repeatable SMR positioning, adversely affecting measurement precision and the traceability of research outcomes. To address these challenges, we investigated alternative methods for attaching an SMR to a robot’s flange to achieve both accuracy and repeatability. Additionally, we analysed measurement errors introduced when using a tool to attach the SMR to the flange. As a solution, we developed a 3D-printed mount designed for attachment to the flange. The mount’s accuracy was evaluated by assessing its eccentricity and the repeatability of the SMR placement. Experimental results demonstrated that the mount achieved an eccentricity radius of 0.35 mm and repeatability inaccuracies of X=0.075mm, Y=0.328mm, and Z=0.485mm. These values indicate that the mount provides sufficient accuracy to support calibration processes, ensures research traceability, and serves as a viable replacement for adhesive bonds.

This paper presents tailored sessions in a robotics laboratory course for undergraduate students. Each session is designed to help the students of different skill levels to gain practical experience, deepen their existing knowledge and learn robotics fundamentals such as Robot Operating System (ROS). With the help of a student survey, it could be shown that the division to well-balanced groups, an incremental structure of the exercises and a selection of different exercise types ensure this.

Discarded wind turbine blades generate a considerable amount of waste that could be reduced by remanufacturing. Manual remanufacturing is too costly, which is why research is being conducted into automation techniques. The main problem is the individuality of work pieces due to damages. This work presents a workflow that includes damage analysis based on scans of the blade, subsequent path planning, control engineering with an AI controller for grinding and automatic review of the grinding process. Current problems are the inaccuracy of the robot used for scanning and the colour sensitivity of the used laser scanner. Our next steps besides solving the mentioned problems are to train a supervised machine learning algorithm with damage examples and to implement a specific and multi-step path planning algorithm.

Static robot calibration determines the parameters of a mathematical model that approximates as closely as possible the relationship between the end-effector pose of a robot and its corresponding actuated joint variables. The manufacturer of a robot delivers such a set of parameters but in principle more accurate own measurements can be used to determine optimized parameters. The purpose of this paper is 1. to show how much the position accuracy of robots of type UR5e from Universal Robots can be increased by application of a marker based optical measurement procedure based on circle fits and 2. what are the limitations of this procedure. Furthermore it is described how to use so called modified Denavit-Hartenberg parameters instead of the typically used distal/classical definition to achieve comparability between different measurements. Overall it is shown that with the calibration procedure the errors can be reduced in practice but only less for a a brand-new robot and with usage of the manufacturer calibration data set. The remaining errors show a specific structure, which suggests that the mechanical stability of the robot limits the positioning accuracy and not the accuracy of the measurement procedure to determine the DH-parameters.

Human robot collaboration is becomming more common, both in industrial and service robotics. This implies robot-human handover tasks, which should respect ergonomic aspects. The robot should adapt to the human and his individual properties. Before handling an object to human, the robot should know, where the exchange should take place best. The determination of such handling positions is crucial. In this study a method is developed and implemented to define and to determine comfort zones for robot-human handover tasks based on optical 3D motion analysis. For demonstration purpose an application is implemented, which determines individualized comfortable takeover positions based on data from RGB-depth cameras.

Small humps on the floor go beyond the detectable scope of laser scanners and are therefore not integrated into SLAM based maps of mobile robots. However, even such small irregularities can have a tremendous effect on the robot's stability and the path quality. As a basis to develop anomaly detection algorithms, kinematics data is collected exemplarily for an overrun of a cable channel and a bulb plate. A recurrent neuronal network (RNN), based on the autoencoder principle, could be trained successfully with this data. The described RNN architecture looks promising to be used for realtime anomaly detection and also to quantify path quality.

This paper contributes to a mechanical/kinematical design of a stair climbing robot. Based on the known Klann-mechanism, an extended re-configurable mechanism is proposed, in order to address the stair climbing problem. Steps offer a great variety of occurrences, since they differ in height, width or step length. Regarding staircases the variety is even higher since they differ in the number of steps per level, the size of the platform, the orientation etc. Due to these variations the concept proposes a re-configurable design, which is tested in simulation and in a real physical setup.