This paper extends the topic of monocular pose estimation of an object using Aruco tags imaged by RGB cameras. The accuracy of the Open CV Camera calibration and Aruco pose estimation pipelines is tested in detail by performing standardized tests with multiple Intel Realsense D435 Cameras. Analyzing the results led to a way to significantly improve the performance of Aruco tag localization which involved designing a 3D Aruco board, which is a set of Aruco tags placed at an angle to each other, and developing a library to combine the pose data from the individual tags for both higher accuracy and stability.

This paper presents an approach to compensate for the effect of thermal expansion on the structure of an industrial robot and thus to reduce the repeatability difference of the robot in cold and warm conditions. In contrast to previous research in this area that deals with absolute accuracy, this article is focused on determining achievable repeatability. To unify and to increase the robot repeatability, the measurements with highly accurate sensors were performed under different conditions on an industrial robot ABB IRB1200, which was equipped with thermal sensors, mounted on a pre-defined position around joints. The performed measurements allowed to implement a temperature-based prediction model of the end effector positioning error. Subsequent tests have shown that the implemented model used for the error compensation proved to be highly effective. Using the methodology presented in this article, the impact of drift can be reduced by up to 89.9%. A robot upgraded with a compensation principle described in this article does not have to be warmed up as it works with the same low repeatability error in the entire range of the achievable temperatures.

Soft gripping, in which the gripper adapts to differently shaped objects, is in great demand for use in unknown or dynamically changing environments and is one of the main research subjects in soft robotics. Several systems have already been created, one of which is a passive shape-adaptable finger based on the FinRay effect. The geometric shape of this finger ensures that the finger wraps around the object it grips. FinRay fingers have been studied in several studies, which have changed the internal structure and examined how gripping force’s dependence on finger deformation changes. So far, however, no specific way has been determined to evaluate the proposed finger regarding its ability to wrap around the object. This work comes up with a new and simple method to evaluate the finger’s wrapping around the object mathematically. Based on this evaluation method, several different patterns of the internal structure of FinRay fingers were tested. The fingers were first tested in a simulation program, which simulated a steel roller indentation with a diameter of 20 mm in the middle of the finger’s contact surface. Based on the simulation results, selected types of structure were made by the Fused Filament Fabrication method from a flexible filament and tested on a real test rig to verify the results of the simulation and compare it with the real behaviour. According to the methodology used, the results show that the most suitable structure of the selected tested fingers from the point of view of wrapping the finger around the object is a structure without internal filling. Designers can simply use the new evaluation method to compare their designed finger variants and select the most suitable one according to the ability to wrap around the gripped object. They can also use graphs from this work’s results and determine the finger’s dimensions without internal filling according to the required forces and deflection.

This study proposes a new approach to improving laser sensor data collection through optimised sensor settings. Specifically, it examines the influence of laser sensor configurations on laser scanning measurements obtained by using a laser line triangulation sensor for transparent and non-transparent plastics, as well as aluminium alloys. Distance data were acquired with a three-degree-of-freedom positioning device and the laser sensor under both manual and automatic settings. Measurements were performed at the sensor’s reference distance and across a wide range of positional configurations. The results of extensive experimental tests highlight optimal sensor configurations for various materials and sensor orientations relative to the scanned surface, including both in-plane and out-of-plane angles, to enhance the reliability and accuracy of distance data collection.

3D printing technology plays a key role in the design of prototypes and final parts. The ability to quickly and easily produce almost any shape using the Fused Filament Fabrication (FFF) method is used in almost every industrial sector, scienc...

The paper deals with methods of equivalence of boundary conditions in finite element models that are based on finite element model updating technique. The proposed methods are based on the determination of the stiffness parameters in the section plate or region, where the boundary condition or the removed part of the model is replaced by the bushing connector. Two methods for determining its elastic properties are described. In the first case, the stiffness coefficients are determined by a series of static finite element analyses that are used to obtain the response of the removed part to the six basic types of loads. The second method is a combination of experimental and numerical approaches. The natural frequencies obtained by the measurement are used in finite element (FE) optimization, in which the response of the model is tuned by changing the stiffness coefficients of the bushing. Both methods provide a good estimate of the stiffness at the region where the model is replaced by an equivalent boundary condition. This increases the accuracy of the numerical model and also saves computational time and capacity due to element reduction.