Open Access

Human-machine interaction can be supported by the detection of humans through the simultaneous localization and distinction from non-human objects. This paper compares modern object detection algorithms (Damo-YOLO, YOLOv6, YOLOv7 and YOLOv8) in combination with Transfer Learning and Super Resolution in different scenarios to achieve human detection on low resolution infrared images. The data set created for this purpose includes images of an empty room, images of warm coffee cups, and images of people in various scenarios and at distances ranging from two to six meters. The Average Precision AP@50 and AP@50:95 values achieved across all scenarios reach up to 98.02 % and 66.99 % respectively.

The objective of this work is to automate thread cutting of internal threads using an industrial robot. The system is designed to accommodate various sheet sizes based on the robot's working range. The robot controller records the data of axis 6 during the cutting process, which will be applied for process and quality analysis. This axis was utilised for the cutting process. An optical displacement sensor determines the accuracy of the moving axis. The robot's endlessly rotating axis 6 offers further advantages, including no additional drive for cutting, maximum flexibility, high automation, and a large working range of up to 800 ∙ 800 mm depending on the robot. The maximum torque derived from the cutting process was 3.52 Nm. The radial movement of the chuck was measured at ∆r = 0.27 mm, which was 60 times higher than the planned data.

Background: Assistive Robotic Arms are designed to assist physically disabled people with daily activities. Existing joysticks and head controls are not applicable for severely disabled people such as people with Locked-in Syndrome. Therefore, eye tracking control is part of ongoing research. The related literature spans many disciplines, creating a heterogeneous field that makes it difficult to gain an overview. Objectives: This work focuses on ARAs that are controlled by gaze and eye movements. By answering the research questions, this paper provides details on the design of the systems, a comparison of input modalities, methods for measuring the performance of these controls, and an outlook on research areas that gained interest in recent years. Methods: This review was conducted as outlined in the PRISMA 2020 Statement. After identifying a wide range of approaches in use the authors decided to use the PRISMA-ScR extension for a scoping review to present the results. The identification process was carried out by screening three databases. After the screening process, a snowball search was conducted. Results: 39 articles and 6 reviews were included in this article. Characteristics related to the system and study design were extracted and presented divided into three groups based on the use of eye tracking. Conclusion: This paper aims to provide an overview for researchers new to the field by offering insight into eye tracking based robot controllers. We have identified open questions that need to be answered in order to provide people with severe motor function loss with systems that are highly useable and accessible.

Printed circuit boards (PCB) are a foundation of electronical devices in modern society. The fabrication of these boards requires various processes and machines. The utilisation of a robot with multiple tools can shorten the process chain compared to screen printing. In this paper a system is presented, which utilises an industrial six axis robot to manufacture PCBs. The process flow and conversion process of the Gerber format into robot specific commands is presented. The advantages and challenges applying a robot to print circuits are discussed.

During the last ten years the development of wireless sensing applications has become more and more attractive. A major reason for this trend is the large quantity of available wireless technologies. The progressing demand on wireless technologies is mainly driven through development from the industrial wireless sensors market. Especially requirements like low energy consumption, a resource saving simple protocol stack and short timing delays between different states of the wireless transceivers are very important for wireless sensors. Bluetooth Low Energy (BLE) is a rather new wireless standard in addition to the traditional Bluetooth standard (Basis rate and enhanced data rate, BR/EDR) [1]. The BLE will completely fulfill these fundamental requirements. First BLE transceiver chips and modules are available and have been tested and implemented in products. In this paper the performance analysis results of a BLE sensor system which is based on the TI transceiver CC2540F [5] will be presented. The results can be taken for further important investigations like lifetime calculations or BLE simulation models.

Human–robot collaborative applications have been receiving increasing attention in industrial applications. The efficiency of the applications is often quite low compared to traditional robotic applications without human interaction. Especially for applications that use speed and separation monitoring, there is potential to increase the efficiency with a cost-effective and easy to implement method. In this paper, we proposed to add human–machine differentiation to the speed and separation monitoring in human–robot collaborative applications. The formula for the protective separation distance was extended with a variable for the kind of object that approaches the robot. Different sensors for differentiation of human and non-human objects are presented. Thermal cameras are used to take measurements in a proof of concept. Through differentiation of human and non-human objects, it is possible to decrease the protective separation distance between the robot and the object and therefore increase the overall efficiency of the collaborative application.

Efficient collaborative robotic applications need a combination of speed and separation monitoring, and power and force limiting operations. While most collaborative robots have built-in sensors for power and force limiting operations, there are none with built-in sensor systems for speed and separation monitoring. This paper proposes a system for speed and separation monitoring directly from the gripper of the robot. It can monitor separation distances of up to three meters. We used single-pixel Time-of-Flight sensors to measure the separation distance between the gripper and the next obstacle perpendicular to it. This is the first system capable of measuring separation distances of up to three meters directly from the robot's gripper.

A novel Bluetooth Low Energy advertising scan algorithm is presented for hybrid radios that are additionally capable to measure energy on Bluetooth channels, e.g. as they would need to be compliant with IEEE 802.15.4. Scanners applying this algorithm can achieve a low latency whilst consuming only a fraction of the power that existing mechanisms can achieve at a similar latency. Furthermore, the power consumption can scale with the incoming network traffic and in contrast to the existing mechanisms, scanners can operate without any frame loss given ideal network conditions. The algorithm does not require any changes to advertisers, hence, stays compatible with existing devices. Performance evaluated via simulation and experiments on real hardware shows a 37 percent lower power consumption compared to the best existing scan setting while even achieving a slightly lower latency which proves that this algorithm can be used to improve the quality of service of connection-less Bluetooth communication or reduce the connection establishment time of connection-oriented communication.

Avoiding collisions between a robot arm and any obstacle in its path is essential to human-robot collaboration. Multiple systems are available that can detect obstacles in the robot's way prior and subsequent to a collision. The systems work well in different areas surrounding the robot. One area that is difficult to handle is the area that is hidden by the robot arm. This paper focuses on pick and place maneuvers, especially on obstacle detection in between the robot arm and the table that robot is located on. It introduces the use of single pixel time-of-flight sensors to detect obstacles directly from the robot arm. The proposed approach reduces the complexity of the problem by locking axes of the robot that are not needed for the pick and place movement. The comparison of simulated results and laboratory measurements show concordance.

Human-robot collaboration plays a strong role in industrial production processes. The ISO/TS 15066 defines four different methods of collaboration between humans and robots. So far, there was no robotic system available that incorporates all four collaboration methods at once. Especially for the speed and separation monitoring, there was no sensor system available that can easily be attached directly to an off-the-shelf industrial robot arm and that is capable of detecting obstacles in distances from a few millimeters up to five meters. This paper presented first results of using a 3D time-of-flight camera directly on an industrial robot arm for obstacle detection in human-robot collaboration. We attached a Visionary-T camera from SICK to the flange of a KUKA LBR iiwa 7 R800. With Matlab, we evaluated the pictures and found that it works very well for detecting obstacles in a distance range starting from 0.5 m and up to 5 m.