As the importance of artificial intelligence grows rapidly and emerges as a leader in technology, it is becoming an important variable in the next-generation industrial system along with the robot industry. In this study, a safety system was developed using deep learning technology to provide worker safety in a robot workplace environment. The implemented safety system has multiple cameras installed with various viewing directions to avoid blind spots caused by interference. Workers in various scenario situations were detected, and appropriate robot response scenarios were implemented according to the worker's risk level through IO communication. For human detection, the YOLO algorithm, which is widely used in object detection, was used, and a separate robot class was added and learned to compensate for the problem of misrecognizing the robot as a human. The performance of the implemented system was evaluated by operator detection performance by applying various operator scenarios, and it was confirmed that the safety system operated stably.

This paper deals with the stability of industrial robot arms with six axes and six degrees of freedom. The robot arm used was IRB120, a product of ABB company, which is used in the real industry, by using the commercial “DAFUL” which is a simulation program that can analyze the dynamic behavior. DAFUL was applied to the robot arm to control the motion by applying the load to the robot arm and then the structural analysis of the robot arm was performed during the analysis time. As a result of the analysis of the robot arm, the stress and displacement acting on the elliptic model and the acting torque and force were analyzed. Based on the analysis results, stability was checked with reference to IRB120 product catalog.

본 연구는 세계 42개국의 자료를 사용하여 산업용 로봇 도입의 결정요인을 분석하고, 한국에서 산업용 로봇이 빠르게 확산되고 있는 원인을 진단하였다. 산업용 로봇 변수는 국제로봇협회(IFR)의 2001년-2016년 「World Robotics: Industrial Robots」 자료를 사용하였다. 설명변수는 노동시장환경 변수와 혁신역량 변수를 포함하며, 관련 변수들은 해당 국제기관들의 자료에서 추출하였다. 실증분석에는 일부 설명변수의 내생성을 통제하기 위해 Arellano-Bond 동적 패널분석을 사용하였다. 분석결과, 한국은 소득수준이나 고용비용 및 혁신역량 등을 고려하더라도 다른 국가들에 비해 산업용 로봇 도입이 매우 빠르게 확대되어 온 것을 확인할 수 있었다. 이는 수요 측면과 공급 측면 모두에서 그 원인을 찾을 수 있다. 즉, 고용비용 증가 등의 노동시장환경 변화가 산업용 로봇 도입에 대한 기업 수요를 견인하였으며, 경제 전반의 자본집약도 증가와 기업의 혁신역량 증대와 같은 공급 측면 요인 또한 산업용 로봇의 도입을 촉진시켰다.

These days, the interests on the high speed handling robots are increasing because it is important to get down the unit cost of production to get the price competitiveness. The SCARA robot with simple mechanism is more suitable to implement the high speed robot system as well known. The moving parts of SCARA robot have to be designed for high speed. But the structural analysis is induced by the robot links because they drive in high acceleration and deceleration. In this reason, the structural analysis of the high speed SCARA robot is very important in the design process. In this paper, the study on the structural analysis of a high speed SCARA robot has been done and the research results will be introduced.

The use of industrial robots has been one of the most important innovations in production technology in recent years. It is true that robotic techniques, as applied to hazardous operation in industry, have reduced the risk of injury and occupational disease among workers. However, new types of occupational safety and health risks, associated with unpredictable motion patterns and erratic idle times and serious injuries and deaths have occurred due to operator misperception of these robot design and performance characteristics. This paper provides an overview of ergonomic and safety issues which are important in the design of robotic workspaces. Particularly, this study uses MORT(Management oversight and risk tree analysis)as the system's safety technique applied to robotics.

This study presents intelligent deburring system which can transfer the exper's skill to deburring robot through neural network. The expert's skill is expressed as associate mapping between the characteristics of the burr and human expert's action. Under the fundamental idea that the state of the deburring process can be extracted via the visual sense of the human, we employ vision system for the perception and identification of the changing burr. From the demonstration of human experts, force data are measured and fitted impedance model. Finally the characteristics of the burr and coressponding force are associated by the neural network which is trained through many demonstrations. The proposed method is verified in the deburring process of welding burr.

This paper presents a dynamic compensation methodology for robust trajectory tracking control of uncertain robot manipulators. To improve tracking performance of the system, a full model-based feedforward compensation with continuous VS-type robust control is developed in this paper(i.e,. robust decentralized adaptive control scheme). Since possible bounds of uncertainties are unknown, the adaptive bounds of the robust control is used to directly estimate the uncertainty bounds(instead of estimating manipulator parameters as in centralized adaptive control0. The global stability and robustness issues of the proposed control algorithm have been investigated extensively and rigorously via a Lyapunov method. The presented control algorithm guarantees that all system responses are uniformly ultimately bounded. Thus, it is shown that the control system is evaluated to be highly robust with respect to significant uncertainties.

Recently, development of robot technology has been actively investigated that industrial robots are used in various other fields. However, the interface of the industrial robot is limited to the planned and manipulated path according to the target point and reaching time of the robot arm. Thus, it is not easy to create or change the various paths of the robot arm in other applications, and it is not easy to control the robot so that the robot arm passes the specific point precisely at the desired time during the course of the path. In order to overcome these limitations, this paper proposes a new-media content management platform that can manipulate 6 DOF industrial robot arm using 3D game engine. In this platform, the user can directly generate the motion of the robot arm in the UI based on the 3D game engine, and can drive the robot in real time with the generated motion. The proposed platform was verified using 3D game engine Unity3D and KUKA KR-120 robot.

Static balance of an articulated robot arm at various configurations requires a torque compensating for the gravitational torque of each joint due to the robot mass. Such compensation torque can be provided by a spring-based counterbalance mechanism. However, simple installation of a counterbalance mechanism at each pitch joint does not work because the gravitational torque at each joint is dependent on other joints. In this paper, a 6 DOF industrial robot arm based on the parallelogram for multi-DOF counterbalancing is proposed to cope with this problem. Two passive counterbalance mechanisms are applied to pitch joints, which reduces the required torque at each joint by compensating the gravitational torque. The performance of this mechanism is evaluated experimentally.

In this article art performing applications of industrial dual-arm robots are introduced. It was real collaboration among robot researchers and artist. Artist designed the performance to use dual-arm robot. Robot researchers collaborated with artist by providing robotic constraints and configuring robot motion. Two art performances were configured with two industrial dual-arm robots. In both performance robots carry objects to be used as moving screens. Both performances rely on the high power and high precision of robots. In addition human-like appearance make those performances be familiar to public

We are at the dawn of a new era in which the importance of robots will be evaluated on the basis of not only their functions but also their appearance. Therefore, those manufacturers who continue to develop robots that only offer convenience and do not keep up with the emerging trends might be weeded out from the robot market in the future. This study empirically tested and verified the ways in which the commercial value of wearable robots is enhanced when they are stylishly attired, using user and work environment analysis. For the purpose of this study, a styling development project for wearable robots was undertaken and applied to the actual development of these robots. Based on the results of the study, a new styling process for such robots was established. Those manufacturers who will realize the importance of styling of robots and develop robots using this process shall become the trendsetters in designing stylized robots and lead the robot industry in the future.

This paper presents a method to optimize motion planning for industrial manipulators with redundancy. For optimal motion planning, first of all, particular inverse kinematic solution is needed to improve efficiency for manipulators with redundancy working in various environments. In this paper, we propose three kinds of methods for solving inverse kinematics problems; numerical and combined approach. Also, we introduce methods for optimal motion planning using potential function considering the order of priority. For efficient movement in industrial settings, this paper presents methods to plan motions by considering colliding obstacles, joint limits, and interference between whole arms. To confirm improved performance of robot applying the proposed algorithms, we use two kinds of robots with redundancy. One is a single arm robot with 7DOF and another is a dual arm robot with 15DOF which consists of left arm, right arm with each 7DOF, and a torso part with 1DOF. The proposed algorithms are verified through several numerical examples as well as by real implementation in robot controllers.