Model-based robust control design and experimental validation of SCARA robot system with uncertainty

In this paper, we design a novel robust control method to reduce the trajectory tracking errors of the SCARA robot with uncertainties including parameters such as uncertainty of the mechanical system and external disturbance, which are time-varying and nonlinear. Then, we propose a deterministic form of the model-based robust control algorithm to deal with the uncertainties. The proposed control algorithm is composed of two parts according to the assumed upper limit of the system uncertainties: one is the traditional proportional-derivative control, and the other is the robust control based on the Lyapunov method, which has the characteristics of model-based and error-based. The stability of the proposed control algorithm is proved by the Lyapunov method theoretically, which shows the system can maintain uniformly bounded and uniformly ultimately bounded. The experimental platform includes the rapid controller prototyping cSPACE, which is designed to reduce programming time and to improve the efficiency of the practical operation. Moreover, we adopt different friction models to investigate the effect of friction on robot performance in robot joints. Finally, numerical simulation and experimental results indicate that the control algorithm proposed in this paper has desired control performance on the SCARA robot.

Comparative Study of Computer Vision Based Line Followers Using Raspberry Pi and Jetson Nano

The line follower robot is a mobile robot which can navigate and traverse to another place by following a trajectory which is generally in the form of black or white lines. This robot can also assist human in carrying out transportation and industrial automation. However, this robot also has several challenges with regard to the calibration issue, incompatibility on wavy surfaces, and also the light sensor placement due to the line width variation. Robot vision utilizes image processing and computer vision technology for recognizing objects and controlling the robot motion. This study discusses the implementation of vision based line follower robot using a camera as the only sensor used to capture objects. A comparison of robot performance employing different CPU controllers, namely Raspberry Pi and Jetson Nano, is made. The image processing uses an edge detection method which detect the border to discriminate two image areas and mark different parts. This method aims to enable the robot to control its motion based on the object captured by the webcam. The results show that the accuracies of the robot employing the Raspberry Pi and Jetson Nano are 96% and 98%, respectively.

Local vs. Avatar Robot: Performance and Perceived Workload of Service Encounters in Public Space

In recent years, the demand for remote services has increased with concerns regarding the spread of infectious diseases and employees’ quality of life. Many attempts have been made to enable store staff to provide various services remotely via avatars displayed to on-site customers. However, the workload required on the part of service staff by the emerging new work style of operating avatar robots remains a concern. No study has compared the performance and perceived workload of the same staff working locally versus remotely via an avatar. In this study, we conducted an experiment to identify differences between the performance of in-person services and remote work through an avatar robot in an actual public space. The results showed that there were significant differences in the partial performance between working via an avatar and working locally, and we could not find significant difference in the overall performance. On the other hand, the perceived workload was significantly lower when the avatar robot was used. We also found that customers reacted differently to the robots and to the in-person participants. In addition, the workload perceived by operators in the robotic task was correlated with their personality and experience. To the best of our knowledge, this study is the first investigation of both performance and workload in remote customer service through robotic avatars, and it has important implications for the implementation of avatar robots in service settings.

Impact analysis of actuator torque degradation on the IRB 120 robot performance using simscape-based model

Actuators in a robot system may become faulty during their life cycle. Locked joints, free-moving joints, and the loss of actuator torque are common faulty types of robot joints where the actuators fail. Locked and free-moving joint issues are addressed by many published articles, whereas the actuator torque loss still opens attractive investigation challenges. The objectives of this study are to classify the loss of robot actuator torque, named actuator torque degradation, into three different cases: Boundary degradation of torque, boundary degradation of torque rate, and proportional degradation of torque, and to analyze their impact on the performance of a typical 6-DOF robot (i.e., the IRB 120 robot). Typically, controllers of robots are not pre-designed specifically for anticipating these faults. To isolate and focus on the impact of only actuator torque degradation faults, all robot parameters are assumed to be known precisely, and a popular closed-loop controller is used to investigate the robot’s responses under these faults. By exploiting MATLAB-the reliable simulation environment, a simscape-based quasi-physical model of the robot is built and utilized instead of an actual expensive prototype. The simulation results indicate that the robot responses cannot follow the desired path properly in most fault cases.

Development of a Modular Tensegrity Robot Arm Capable of Continuous Bending

In this study, we present a tensegrity robot arm that can reproduce the features of complex musculoskeletal structures, and can bend like a continuum manipulator. In particular, we propose a design method for an arm-type tensegrity robot that has a long shape in one direction, and can be deformed like a continuum manipulator. This method is based on the idea of utilizing simple and flexible strict tensegrity modules, and connecting them recursively so that they remain strict tensegrity even after being connected. The tensegrity obtained by this method strongly resists compressive forces in the longitudinal direction, but is flexible in the bending direction. Therefore, the changes in stiffness owing to internal forces, such as in musculoskeletal robots, appear more in the bending direction. First, this study describes this design method, then describes a developed pneumatically driven tensegrity robot arm with 20 actuators. Next, the range of motion and stiffness under various driving patterns are presented as evaluations of the robot performance.

Modeling of a Mobile Spatial Cable Robot With Flexible Cables and Investigating the Effect of Its Nonlinear Vibrations on the System Dynamics

In this paper the modeling of a novel moving cable robot is conducted considering the vibration of the cables in its nonlinear format. The robot has 6 DOFs while the controlling input number is 12. Considering the fact that the elasticity of the cables is coupled with the dynamic model of the system, their vibration effects on the robot performance and accuracy. The target of this paper is to model the robot considering the cables’ elasticity and study its effect on the robot performance. This study can be considered in designing the controller of tower cranes and decrease the swing of the cables and increasing their stability. In order to cover the mentioned aim, the continuous vibration of the cables are modeled as a nonlinear system and it is added to the moving platform dynamics. Moreover the differences between the nonlinear modeling of the cables’ vibration and estimating them as a linear system is studied and their related results are compared and analyzed. The correctness of modeling is shown by comparing the results with previous research and the superiority of modeling the cables’ vibration in its nonlinear format is verified by the aid of a series of simulation scenarios in MATLAB. Moreover, by conducting some experimental test on the manufactured moving cable robot of IUST, it is illustrated that, modeling the cables in these robots as a nonlinear system results in more accurate results. It is shown that not only considering the cables’ vibration is significant in analyzing the robot dynamic, but also it is shown that promoting the mentioned model into nonlinear one increase the accuracy of the robot modeling which sequentially can provide a stronger controller for stabilizing and controlling the end-effector within a predefined trajectory.

Increasing the operating depth of an autonomous underwater vehicle using an intelligent magnetic field

<p>Designing and manufacturing a suitable body is one of the most effective factors in increasing the efficiency of autonomous underwater vehicles (AUVs). In fact, increasing the propulsive power of an AUV by reducing the frictional drag on its body and incre asing its maneuverability will positively affect key parts of the AUV’s hardware and software such as control system, sensors, AUV vision, batteries and thrusters. On the other hand, a suitable body should have features such as lightness, underwater vehicl e’s balance, high mechanical strength, and enough space for equipment. Therefore, the design and manufacture of the body requires a lot of analysis in terms of body material, aerodynamic calculations, etc., increases the overall cost. This paper aims to re duce the stress in the body of a Polytetrafluoroethylene ( PTFE ) underwater robot and to increase its operating depth without changing the body’s structure by using fuzzy logic to intelligently controlling the magnetic force generated by the repulsion betwe en the coil and the cylindrical magnet, which saves energy, reduces battery consumption, and increases system performance. The results show that the robot performance depth increases by more than 50% without changing the robot body structure.</p>

Trends and Progress in Collaborative Robot Applications

Modern robots have been used in different applications including welding, painting, soldering, assembly of different products and in education. List of applications is getting even longer because robot performance is improving. Faculties are following industries involving robots in their curriculum, while industry is interested in new ideas including new applications and their improvements from the university. Modern robots are user-friendly for programming so the lack of knowledge about robot applications seems to be the main obstacle in their wider implementation. Collaborative robots or cobots are sophisticated robots which could operate with other robots and with workers in the factory. Recent opening of Yaskawa factory in Kočevje, Slovenia, near border with Croatia, has significant impact on integrating the robots in production and education in central and South-east Europe.

Embodiment and Its Influence on Informational Costs of Decision Density—Atomic Actions vs. Scripted Sequences

The importance of embodiment for effective robot performance has been postulated for a long time. Despite this, only relatively recently concrete quantitative models were put forward to characterize the advantages provided by a well-chosen embodiment. We here use one of these models, based on the concept of relevant information, to identify in a minimalistic scenario how and when embodiment affects the decision density. Concretely, we study how embodiment affects information costs when, instead of atomic actions, scripts are introduced, that is, predefined action sequences. Their inclusion can be treated as a straightforward extension of the basic action space. We will demonstrate the effect on informational decision cost of utilizing scripts vs. basic actions using a simple navigation task. Importantly, we will also employ a world with “mislabeled” actions, which we will call a “twisted” world. This is a model which had been used in an earlier study of the influence of embodiment on decision costs. It will turn out that twisted scenarios, as opposed to well-labeled (“embodied”) ones, are significantly more costly in terms of relevant information. This cost is further worsened when the agent is forced to lower the decision density by employing scripts (once a script is triggered, no decisions are taken until the script has run to its end). This adds to our understanding why well-embodied (interpreted in our model as well-labeled) agents should be preferable, in a quantifiable, objective sense.