In this analysis, we present results from measurements performed to determine the stability of a hand tracking system and the accuracy of the detected palm and finger’s position. Measurements were performed for the evaluation of the sensor for an application in an industrial robot-assisted assembly scenario. Human–robot interaction is a relevant topic in collaborative robotics. Intuitive and straightforward control tools for robot navigation and program flow control are essential for effective utilisation in production scenarios without unnecessary slowdowns caused by the operator. For the hand tracking and gesture-based control, it is necessary to know the sensor’s accuracy. For gesture recognition with a moving target, the sensor must provide stable tracking results. This paper evaluates the sensor’s real-world performance by measuring the localisation deviations of the hand being tracked as it moves in the workspace.

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.

In this article, the ultra-wideband technology for localization and tracking of the robot gripper (behind the obstacles) in industrial environments is presented. We explore the possibilities of ultra-wideband radar sensor network employing the centralized data fusion method that can significantly improve tracking capabilities in a complex environment. In this article, we present ultra-wideband radar sensor network hardware demonstrator that uses a new wireless ultra-wideband sensor with an embedded controller to detect and track online or off-line movement of the robot gripper. This sensor uses M-sequence ultra-wideband radars front-end and low-cost powerful processors on a system on chip with the advanced RISC machines (ARM) architecture as a main signal processing block. The ARM-based single board computer ODROID-XU4 platform used in our ultra-wideband sensor can provide processing power for the preprocessing of received raw radar signals, algorithms for detection and estimation of target’s coordinates, and finally, compression of data sent to the data fusion center. Data streams of compressed target coordinates are sent from each sensor node to the data fusion center in the central node using standard the wireless local area network (WLAN) interface that is the feature of the ODROID-XU4 platform. The article contains experimental results from measurements where sensors and antennas are located behind the wall or opaque material. Experimental testing confirmed capability of real-time performance of developed ultra-wideband radar sensor network hardware and acceptable precision of software. The introduced modular architecture of ultra-wideband radar sensor network can be used for fast development and testing of new real-time localization and tracking applications in industrial environments.

No abstract

Robotic football with humanoid robots is a multidisciplinary field connecting several scientific fields. A challenging task in the design of a humanoid robot for the AndroSot and HuroCup competitions is the realization of movement on the field. This study aims to determine a walking pattern for a humanoid robot with an impact on its dynamic stability and behavior. The design of the proposed technical concept depends on its stability management mechanism, walking speed and such factors as the chosen stability approaches. The humanoid robot and its versatility, along with the adaptability of the terrain, are somewhat limited due to the complexity of the walking principle and the control of the robot’s movement itself. The technical concept uses dynamic stability as the potential force of the inertial bodies and their parts so that the humanoid robot does not overturn. The total height of the robot according to the rules of the competition will be 50 cm. In the performed experiment, only the lower part of the humanoid robot with added weight was considered, which is more demanding due to the non-use of the upper limbs for stabilization. The performed experiment verified the correctness of the design, where the torso of the robot performed eight steps in inclinations of a roll angle +4/−2° and a pitch angle +4/−6°.