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Artificial intelligence techniques for pneumatic robot manipulators have become of deep interest in industrial applications, such as non-high voltage environments, clean operations, and high power-to-weight ratio tasks. The principal advantages of this type of actuator are the implementation of clean energies, low cost, and easy maintenance. The disadvantages of working with pneumatic actuators are that they have non-linear characteristics. This paper proposes an intelligent controller embedded in a programmable logic device to minimize the non-linearities of the air behavior into a 3-degrees-of-freedom robot with pneumatic actuators. In this case, the device is suitable due to several electric valves, direct current motors signals, automatic controllers, and several neural networks. For every degree of freedom, three neurons adjust the gains for each controller. The learning process is constantly tuning the gain value to reach the minimum of the mean square error. Results plot a more appropriate behavior for a transitive time when the neurons work with the automatic controllers with a minimum mean error of ±1.2 mm.

Achieving the smart motion of any autonomous or semi-autonomous robot requires an efficient algorithm to determine a feasible collision-free path. In this paper, a novel collision-free path homotopy-based path-planning algorithm applied to planar robotic arms is presented. The algorithm utilizes homotopy continuation methods (HCMs) to solve the non-linear algebraic equations system (NAES) that models the robot’s workspace. The method was validated with three case studies with robotic arms in different configurations. For the first case, a robot arm with three links must enter a narrow corridor with two obstacles. For the second case, a six-link robot arm with a gripper is required to take an object inside a narrow corridor with two obstacles. For the third case, a twenty-link arm must take an object inside a maze-like environment. These case studies validated, by simulation, the versatility and capacity of the proposed path-planning algorithm. The results show that the CPU time is dozens of milliseconds with a memory consumption less than 4.5 kB for the first two cases. For the third case, the CPU time is around 2.7 s and the memory consumption around 18 kB. Finally, the method’s performance was further validated using the industrial robot arm CRS CataLyst-5 by Thermo Electron.

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Computer vision-based path planning can play a crucial role in numerous technologically driven smart applications. Although various path planning methods have been proposed, limitations, such as unreliable three-dimensional (3D) localization of objects in a workspace, time-consuming computational processes, and limited two-dimensional workspaces, remain. Studies to address these problems have achieved some success, but many of these problems persist. Therefore, in this study, which is an extension of our previous paper, a novel path planning approach that combined computer vision, Q-learning, and neural networks was developed to overcome these limitations. The proposed computer vision-neural network algorithm was fed by two images from two views to obtain accurate spatial coordinates of objects in real time. Next, Q-learning was used to determine a sequence of simple actions: up, down, left, right, backward, and forward, from the start point to the target point in a 3D workspace. Finally, a trained neural network was used to determine a sequence of joint angles according to the identified actions. Simulation and experimental test results revealed that the proposed combination of 3D object detection, an agent-environment interaction in the Q-learning phase, and simple joint angle computation by trained neural networks considerably alleviated the limitations of previous studies.

The main focus of this paper is to design and develop a system of two robot arms for classifying and sorting objects based on shape and size using machine vision. The system uses a low-cost and high-performance hierarchical control system including one master and two slaves. Each slave is a robot controller based on a microcontroller that receives commands from the master to control the robot arm independently. The master is an embedded computer used for image processing, kinematic calculations, and communication. A simple and efficient image processing algorithm is proposed that can be implemented in real-time, helping to shorten the time of the sorting process. The proposed method uses a series of algorithms including contour finding, border extraction, centroid algorithm, and shape threshold to recognize objects and eliminate noise. The 3D coordinates of objects are estimated just by solving a linear equation system. Movements of the robot's joints are planned to follow a trapezoidal profile with the acceleration/deceleration phase, thus helping the robots move smoothly and reduce vibration. Experimental evaluation reveals the effectiveness and accuracy of the robotic vision system in the sorting process. The system can be used in the industrial process to reduce the required time to achieve the task of the production line, leading to improve the performance of the production line.

The paper presents some building schemas of manipulator-robots used in auxiliary operations of electric arc furnaces that are found insteel works. The technology of making steel in electric arc furnaces requires thatthe liquid steel outlet is filledfollowing theprimary elaboration. An "EBT SAND" type manipulator is used to fill the steel outlet, the kinematic scheme of which corresponds toSCARA robots. To unlock the steel outlet, an "EBT STAP" type manipulator is used, which is equipped with an oxygen lance to open the tap-hole. To clean the furnace outlet following the discharge, an "EBT STROP" type manipulator is used to allow the correct reconditioning of the tap-hole. It consists ofan electrically driven swing arm and a hydraulic lift that cleansthe EBT tap-hole.

Background and Objectives: This paper presents a new optimization problem in the field of linkage reconfiguration. This is the problem of minimizing moving parts of a given robot arm for positioning the end effector of the given robot arm at the given target point as well as minimizing the movement of the movable parts. Methods: Initially, formal modeling is accomplished by minimizing the movement problem. At this time, a criterion called AM (Arithmetic Measure) is introduced, and this criterion is used to quantify the motion of the linkage. Afterward, it is indicated that the presented problem is an NP-Hard problem. Consequently, a greedy heuristic algorithm is presented to minimize the movement of the robot's moving components. After identifying the moving components and the movement of these parts, an algorithm is provided to determine the final configuration of the robot arm. Results: The results indicate that the discussed model successfully reduced the moving parts of the robot arm. Moreover, the results show that the proposed approach fulfills the goal of minimization of the linkage components. Furthermore, this method leads to erosion of arm, reduces energy consumption and the required parameters and variables for calculating the final configuration of the linkages. Conclusion: The mentioned algorithm solves the problem by mapping the robot arm with an arbitrary number of links to a robot with a single link or two links. The proposed heuristic approach requires O(n2) time using O(n) space.======================================================================================================Copyrights©2018 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.======================================================================================================

In this study, a real time monitoring and control of the working parameters of distributed robotic systems used in manufacturing processes is presented. Additionally, a fault diagnosis and protection system is developed in the control and monitoring system to prevent possible errors during the working process. Unlike the conventional monitoring and control systems, Android/IOS based smart phones and tablets are used besides SCADA and the process is supported by cameras. 3 different robotic systems are used in the study and electrical, electronic and mechanical prototypes are designed for each of them. Thus, a complete robotic system being able to perform real time monitoring and control for industrial manufacturing processes that is supported by smart phone applications and fault diagnosis and protection system is developed successfully.

As systems become increasingly complex, their simulation techniques have to be more accurate and enhanced. Despite the wide use of robotic arms in industries, they still encompass a wide number of complexities. The control of a flexible robot arm driven by a Brushless DC Motor (BDCM) for tracking problems is a great challenge, not only for its complex algorithms but also for its verification process. Robotic systems are designed heterogeneously by combining continuous and event discrete models. Therefore, computer-aided engineering tools have to be enhanced in order to support the verification of the control algorithms. Ensuring definite and rapid simulations is a challenging task for robotic application systems. Although control strategies can be tested using the Matlab/Simulink environment to assess their performance, their verification at a low-level still remains a very difficult task. This paper studies different simulation techniques based on Model In the Loop (MIL), Hardware In the Loop (HIL), and Hardware Software In the Loop (HSIL) on a flexible robot arm driven by BDCM in order to overcome each method's limits, focusing on performance and cost and simulation time reduction. The HSIL achieves the highest accuracy and speed than MIL and HIL and provides reusability and portability of the control unit compared to the other techniques. [ABSTRACT FROM AUTHOR]

This study proposes an automatic recognition and location system of electric vehicle charging port with application to automatic charging. The system obtains the charging port posture through image processing, and performs the insertion motion in combination with the robot arm to complete the charging gun insertion of the automatic charging link. The framework of the system is mainly divided into three parts, recognition, location and insertion. In the charging port recognition, the convolutional neural network‐based method is used, and the recognition success rate is up to 98.9% under the light intensity of 4000 lux; in the location of the charging port, the method of solving the pose based on the circle feature is adopted. The average value of the position error is within 1.4 mm, and the average value of the attitude angle error is within 1.6°, which meets the accuracy requirement of the insertion experiment; in the charging gun insertion, the motion of the robot is planned by interpolation algorithm. The lower limit of the successful insertion is about 135 lux and the upper limit is about 9350 lux. [ABSTRACT FROM AUTHOR]

Electro-hydrostatic actuator (EHA) has backdrivability and is suitable for a robot system that cooperates with human. However, its design methodology to miniaturize and to generate high pressure has not been established. We develop a robotic arm, all joints of which are actuated by EHAs. This paper reports the development of the vane motor type EHA and a wrist mechanism using the EHA. We employ a single vane motor for a wide motion range. In order to suppress internal leakage, we carefully set the clearance of the EHA and made the rigid casing by using ceramics disks. It is confirmed that the internal leakage of the new EHA is significantly reduced compared to that of the previous model. The wrist mechanism has three degrees of freedom, consisting of three vane motors in series. The flow path between a hydraulic pump and a vane motor is designed using metal pipings, swivel joints and manifolds are presented for a compact wrist mechanism. We validated the fundamental performance of the developed wrist mechanism through experiments. [ABSTRACT FROM AUTHOR]

Ａｉｍｉｎｇ ａｔ ｔｈｅ ｃｏｎｔｒｏｌ ｉｓｓｕｅｓ ｆｏｒ ｐｏｓｉｔｉｏｎ ａｎｄ ｐｏｓｔｕｒｅ ａｄｊｕｓｔｍｅｎｔꎬ ｃｏｎｔａｃｔ ｓｔｒｅｓｓꎬ ｕｎｌｏａｄｉｎｇ ｇｒａｖｉｔｙ ｄｕｒｉｎｇ ｌａｒｇｅ ｃｏｍｐｏｎｅｎｔ ｏｒ ｈｅａｖｙ ｐａｙｌｏａｄ ａｓｓｅｍｂｌｙ ｔｏ ｔｈｅ ｓａｔｅｌｌｉｔｅꎬ ｔｈｅ ｔｅｃｈｎｏｌｏｇｙ ｏｆ ｒｏｂｏｔ ａｒｍ ａｉｄｅｄ ａｓｓｅｍｂｌｙ ｗａｓ ａｐｐｌｉｅｄ. Ａ ｃｏｍｐｌｉａｎｔ ａｓｓｅｍｂｌｙ ｔｅｃｈｎｏｌｏｇｙ ｗｉｔｈ ｒｏｂｏｔ ａｒｍ ａｓｓｉｓｔａｎｃｅ ｂａｓｅｄ ｏｎ ｆｏｒｃｅ ｓｅｎｓｉｎｇ ｉｎｔｅｒａｃｔｉｖｅ ｃｏｎｔｒｏｌ ｗａｓ ｐｒｅｓｅｎｔｅｄꎬ ｔｈｒｏｕｇｈ ｒｅａｌ￣ｔｉｍｅ ａｃｑｕｉｓｉｔｉｏｎ ｏｆ ｆｏｒｃｅ/ ｔｏｒｑｕｅ ａｔ ｔｈｅ ｅｎｄ ｏｆ ｒｏｂｏｔꎬ ｔｈｅ ｌｏａｄ ｇｒａｖｉｔｙ ｐａｒａｍｅｔｅｒｓ ｗｅｒｅ ｃａｌｉｂｒａｔｅｄꎬ ｅｘｔｅｒｎａｌ ｆｏｒｃｅ/ ｔｏｒｑｕｅ ｗａｓ ｅｘｔｒａｃｔｅｄ. Ｔｈｅｎ ｔｈｅ ｃｏｍｐｌｉａｎｔ ｆｏｌｌｏｗ￣ｕｐ ａｌｇｏｒｉｔｈｍ ｏｆ ａｓｓｅｍｂｌｙ ｐｏｓｉｔｉｏｎ ａｎｄ ｐｏｓ￣ ｔｕｒｅ ｗａｓ ｅｓｔａｂｌｉｓｈｅｄꎬ ｂａｓｅｄ ｏｎ ｅｘｔｅｒｎａｌ ｆｏｒｃｅ/ ｔｏｒｑｕｅ ｃｏｎｔｒｏｌꎬ ｔｈｅ ｄｅｖｉａｔｉｏｎｓ ａｎｄ ｃｏｎｔｒｏｌ ｍｅｔｈｏｄｓ ｏｆ ｔｈｅ ａｌｇｏｒｉｔｈｍ ｗｅｒｅ ａｎａｌｙｚｅｄ. Ｍｅａｎｗｈｉｌｅꎬ ａ ｓｙｓｔｅｍ ｏｆ ｒｏｂｏｔ ａｒｍ ａｓｓｉｓｔｅｄ ｃｏｍｐｌｉａｎｔ ａｓｓｅｍｂｌｙ ｗａｓ ｂｕｉｌｔꎬ ｔｈｅ ａｐｐｌｉｃａｔｉｏｎ ｅｘｐｅｒｉｍｅｎｔｓ ｗｅｒｅ ｃａｒｒｉｅｄ ｏｕｔ ｉｎ ａ ｌａｒｇｅ ｓｔｒｕｃｔｕｒａｌ ｃａｂｉｎ ｐｌａｔｅ ａｎｄ ａ ｈｅａｖｙ ｐａｙｌｏａｄ ａｓｓｅｍｂｌｙ ｔｏ ａ ｓａｔｅｌｌｉｔｅ. Ｔｈｅ ｅｘｐｅｒｉｍｅｎｔａｌ ｒｅｓｕｌｔｓ ｓｈｏｗ ｔｈａｔ ｔｈｅ ｌｏｗｅｒ ｌｉｍｉｔ ｏｆ ｆｏｒｃｅ/ ｔｏｒｑｕｅ ｃｏｎｔｒｏｌ ｒａｎｇｅ ｒｅａｃｈｅｓ １０ Ｎ/２ Ｎｍ. Ｃｏｍｐａｒｅｄ ｗｉｔｈ ｔｒａｄｉｔｉｏｎａｌ ａｓｓｅｍｂｌｙ ｍｅｔｈｏｄꎬ ｔｈｉｓ ｍｅｔｈｏｄ ｈａｓ ｔｈｅ ｆｏｌｌｏｗｉｎｇ ａｄｖａｎｔａｇｅｓ ｏｆ ｃｏｍｐｌｉａｎｔ ａｄｊｕｓｔｍｅｎｔ ｏｆ ｐｏｓｉｔｉｏｎ ａｎｄ ｐｏｓｔｕｒｅꎬ ｃｏｎ￣ ｔｒｏｌｌａｂｌｅ ａｓｓｅｍｂｌｙ ｃｏｎｔａｃｔ ｓｔｒｅｓｓꎬ ａｃｃｕｒａｔｅｌｙ ｃａｒｒｙｉｎｇ ａｎｄ ｕｎｌｏａｄｉｎｇ ｇｒａｖｉｔｙꎬ ｓｕｉｔａｂｉｌｉｔｙ ｆｏｒ ａｓｓｅｍｂｌｙ ｗｉｔｈ ａ ｓｐｅｃｉｆｉｃ ｐｏｓｔｕｒｅ ａｍｏｎｇ ｃｏｎｆｉｎｅｄ ｓｐａｃｅ. [ABSTRACT FROM AUTHOR]

In the design optimization of robot arms, the use of simulation technologies for modeling and optimizing the objective functions is still challenging. The difficulty is not only associated with the large computational cost of high-fidelity structural simulations but also linked to the reasonable compromise between the multiple conflicting objectives of robot arms. In this paper we propose a surrogate-based evolutionary optimization (SBEO) method via a global optimization approach, which incorporates the response surface method (RSM) and multi-objective evolutionary algorithm by decomposition (the differential evolution (DE) variant) (MOEA/D-DE) to tackle the shape design optimization problem of robot arms for achieving high speed performance. The computer-aided engineering (CAE) tools such as CAE solvers, computer-aided design (CAD) Inventor, and finite element method (FEM) ANSYS are first used to produce the design and assess the performance of the robot arm. The surrogate model constructed on the basis of Box–Behnken design is then used in the MOEA/D-DE, which includes the process of selection, recombination, and mutation, to optimize the robot arm. The performance of the optimized robot arm is compared with the baseline one to validate the correctness and effectiveness of the proposed method. The results obtained for the adopted example show that the proposed method can not only significantly improve the robot arm performance and save computational cost but may also be deployed to solve other complex design optimization problems. [ABSTRACT FROM AUTHOR]

The area of space immediately around the floral display is likely to have an increased level of humidity relative to the environment around it, due to both nectar evaporation and floral transpiration. This increased level of floral humidity could act as a close-distance cue for pollinators or influence thermoregulation, pollen viability and infection of flowers by fungal pathogens. However, with a few exceptions, not much is known about the patterns of floral humidity in flowering plants or the physiological traits that result in its generation. We conducted a survey of 42 radially symmetrical flower species (representing 21 widely spread families) under controlled conditions. Humidity was measured using a novel robot arm technique that allowed us to take measurements along transects across and above the floral surface. The intensity of floral humidity was found to vary between different flower species. Thirty of the species we surveyed presented levels of humidity exceeding a control comparable to background humidity levels, while twelve species did not. Patterns of floral humidity also differed across species. Nevertheless, floral humidity tended to be highest near the center of the flower, and decreased logarithmically with increasing distance above the flower, normally declining to background levels within 30 mm. It remains unclear how physiological traits influence the diversity of floral humidity discovered in this survey, but floral shape seems to also influence floral humidity. These results demonstrate that floral humidity may occur in a wide range of species and that there might be greater level of diversity and complexity in this floral trait than previously known. [ABSTRACT FROM AUTHOR]

Robots have increasingly replaced humans for many jobs, including 24 h work, routine tasks, and dangerous jobs. However, the robot operating system has high power consumption in many processes. This has led to energy efficiency being the main focus. We have opted to build a robot with high strength, light weight, and low power consumption by reducing the weight of its components. Presently, we know that the structure of most robots in the world is made of metals, plastics, and composite materials. In this research, we designed the mechanical structure of robot arms with three different materials (cast iron, polyamide, and aluminum) using the finite element method to analyze and evaluate the possibilities of these materials. The dynamic load, power consumption, and mechanical characteristics were compared. It was found that polyamide could help lighten the weight by 40% and increase energy efficiency along with cost effectiveness by 41%. Although polyamide is particularly easy to find, cast iron is stronger than polyamide. [ABSTRACT FROM AUTHOR]

Robotics is an interdisciplinary field and there exist several well-known approaches to represent the dynamics model of a robot arm. The robot arm is an open kinematic chain of links connected through rotational and translational joints. In the general case, it is very difficult to obtain explicit expressions for the forces and the torques in the equations where the driving torques of the actuators produce desired motion of the gripper. The robot arm control depends significantly on the accuracy of the dynamic model. In the existing literature, the complexity of the dynamic model is reduced by linearization techniques or techniques like machine learning for the identification of unmodelled dynamics. This paper proposes a novel approach for deriving the equations of motion and the actuator torques of a robot arm with an arbitrary number of joints. The proposed approach for obtaining the dynamic model in closed form employs graph theory and the orthogonality principle, a powerful concept that serves as a generalization for the law of conservation of energy. The application of this approach is demonstrated using a 3D-printed planar robot arm with three degrees of freedom. Computer experiments for this robot are executed to validate the dynamic characteristics of the mathematical model of motion obtained by the application of the proposed approach. The results from the experiments are visualized and discussed in detail.

Path planning for robot arms to reach a target and avoid obstacles has had a crucial role in manufacturing automation. Although many path planning algorithms, including RRT, APF, PRM, and RL-based, have been presented, they have many problems: a time-consuming process, high computational costs, slowness, non-optimal paths, irregular paths, failure to find a path, and complexity. Scholars have tried to address some of these issues. However, those methods still suffer from slowness and complexity. In order to address these two limitations, this paper presents a new hybrid path planning method that contains two separate parts: action-finding (active approach) and angle-finding (passive approach). In the active phase, the Q-learning algorithm is used to find a sequence of simple actions, including up, down, left, and right, to reach the target cell in a gridded workspace. In the passive phase, the joints angles of the robot arm, with respect to the found actions, are obtained by the trained neural network. The simulation and test results show that this hybrid approach significantly improves the slowness and complexity due to using the simplified agent-environment interaction in the active phase and simple computing the joints angles in the passive phase.

The robot arm DH parameter calibration method based on calibration board is proposed,the 7points of calibration board can be sampled by using the end effector in sequence,among which the first 3 points are used to construct the relationship between world and robot coordination system while the other 4 points are applied to establish objective function and error equation. The DH parameter after calibration can be obtained by optimization solution of error equation. At last,the effectiveness of this method is verified through repeated positioning accuracy,the repeated positioning accuracy can be improved from 4. 68 mm to 0. 87 mm. This method has the advantages of simple equipment and easy operation.

By adopting a genetic algorithm for optimization of neural network,the gravity compensation for robot arm is researched.Firstly,through the basic knowledge of mechanics and D-H parameter to set up robot kinematics model,the theoretical computation formula of the gravity item of each joint torque in robot arm is got.Secondly,in the Solid Works simulation software,the simulation value of the gravity item in some certain pose got,thus the correctness of the theoretical computation formula is verified.Finally,the predicted value of the gravity item by genetic algorithm for optimization of neural network is obtained.Experimental results show that the predicted value of gravity items of robot arm learnt with this method is basically conforming with the theoretical value.Consequently,the work load of calculation for the gravity items of robot arm is effectively reduced.Furthermore,this method provide a possible way for the real-time control.

This paper shows a singular mechanism for a gravity compensated and reactionless robot arm. Firstly, the difference between singular point and singular mechanism is explained. A Simple example shows that singular point is local but singular mechanism is global. In other words the latter singularity is globally maintained. Secondly, four characteristics are introduced. The first one is gravity equilibrium, the second is centroid immobility, the third is conservation of angular momentum and the last is constant posture. Gravity compensation is made possible by gravity equilibrium, and no reaction is made possible by centroid immobility and conservation of angular momentum. Thirdly, a robot arm using a singular mechanism is introduced, and characteristics of no reaction are shown by a computer simulation. Finally, it shows the motion range of the arm as an issue.

In the field of regenerative medicine, cell processing is currently done manually. The process is labor intensive and expensive, and its efficiency must be improved. Automatic cell culture apparatuses equipped with a vertical articulated robot have been proposed recently. However, automating all tasks of cell processing complicates the system constitution. The present study aims to develop a simple and rational cell processing system by combining the tasks performed by a robot with those performed by a human. Herein, we first analyze each task in the cell processing operation, verify whether a task can be efficiently performed by a robot and automated equipment, and decide the combination of the tasks. In a previous paper, we improved the efficiency of the task of discarding spent culture media in a flask by using a robot arm in the media change process. In the present paper, by focusing on the media change process, we examine the efficiency improvement of the task of injecting culture media by using a robot. We propose the configuration of an inspiration/injection port and an algorithm to estimate the start time of injection end motion from the flow rate and conduct a verification experiment. Our results show that a robot can perform the injecting task more efficiently than a human. Moreover, the risk of dripping can be reduced by using a robot.

Robot arm monitoring is often required in intelligent industrial scenarios. A two-stage method for robot arm attitude estimation based on multi-view images is proposed. In the first stage, a super-resolution keypoint detection network (SRKDNet) is proposed. The SRKDNet incorporates a subpixel convolution module in the backbone neural network, which can output high-resolution heatmaps for keypoint detection without significantly increasing the computational resource consumption. Efficient virtual and real sampling and SRKDNet training methods are put forward. The SRKDNet is trained with generated virtual data and fine-tuned with real sample data. This method decreases the time and manpower consumed in collecting data in real scenarios and achieves a better generalization effect on real data. A coarse-to-fine dual-SRKDNet detection mechanism is proposed and verified. Full-view and close-up dual SRKDNets are executed to first detect the keypoints and then refine the results. The keypoint detection accuracy, PCK@0.15, for the real robot arm reaches up to 96.07%. In the second stage, an equation system, involving the camera imaging model, the robot arm kinematic model and keypoints with different confidence values, is established to solve the unknown rotation angles of the joints. The proposed confidence-based keypoint screening scheme makes full use of the information redundancy of multi-view images to ensure attitude estimation accuracy. Experiments on a real UR10 robot arm under three views demonstrate that the average estimation error of the joint angles is 0.53 degrees, which is superior to that achieved with the comparison methods.

Machine-vision-based reading and sorting devices have been used to measure and classify items. Here, we extend their application to the sorting and assembling of items identified by their geometry and color. In this study, we developed an improved machine vision system that is capable of discerning and categorizing items of distinct geometries and colors and utilizes a computer-controlled robotic system to manipulate and segregate these items. Hence, a machine vision system for an automatic classification process while operating a robotic arm is hereby developed. To obtain positioning information, the proposed system uses cameras that were mounted above the working platform to acquire images. Perspective and quadratic transformations were used to transform the image coordinates of the calibration system to the world coordinates by using a calibration procedure. By these methods, the proposed system can ascertain the two- and three-dimensional coordinates of the objects and automatically perform classification and assembly operations using the data collected from the visual recognition system. [ABSTRACT FROM AUTHOR]

We describe integrated control of a multiple-degree-of-freedom hand and arm using a simple reactive architecture based on high-speed proximity sensing. A proximity sensor installed on each fingertip of the hand detects the positions between the sensor and the surface of an object. By feeding back the sensor outputs, the reactive architecture simultaneously controls the position of the arm tip and the vector connecting the grasping position and the origin of the arm tip coordinates, the wrist posture, and the initial finger configurations before grasping. This architecture makes it possible to correct position errors. In addition, since the positions and postures are controlled without contact, there is no danger of damaging the object or the robot. To realize this integrated control using a simple reactive architecture, we designed a high-speed proximity sensor for the fingertips of the hand, and developed an integrated control system for the hand and the arm. We demonstrate high-speed position adjustment motion and grasping for static and moving objects in experiments. [ABSTRACT FROM AUTHOR]

In this paper, a novel concept of robust Nonsingular Fast Terminal Sliding Mode controller (NFTSMC) is adopted for the trajectory tracking problem of a non-linear system. The developed controller is based on NFTSM controller and approach. The use of the NFTSM controller offers a fast convergence rate, avoids singularities, but still suffers from chattering. In order to overcome this limitation, a new term in the control law is inspired by the technique of it interferes by managing uncertainties and external disturbances without knowing their upper bound. Stability analysis of the closed-loop system is accomplished using the Lyapunov criterion. Several simulation results are given to show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper presents a humanoid robotic arm massage system with an aim toward satisfying the clinical requirements of pain relief on the waist and legs of older patients during Chinese medicinal massage. On the basis of an in-depth analysis regarding the characteristics of arm joints of the human body and Chinese medicinal massage theory, a humanoid robotic arm massage system was designed by adapting a bottom to top modular method. The combined finite element and kinematic analysis led to an improved performance according to repeated positioning accuracy, massage strength accuracy, and massage effect. The developed humanoid robotic arm was characterized by a compact structure, high precision, light quality, and good stiffness, achieving a good bearing capacity. Due to the PID controller, the numerical simulations and experimental results provided valuable insight into the development of Chinese medicinal massage robots and massage treatments for patients who suffer from lumbar muscle strain. [ABSTRACT FROM AUTHOR]

In this research, the author presents the model of the two-link robot arm and its dynamic equations. Based on these dynamic equations, the author builds the sliding mode controller for each joint of the robot. The tasks of the controllers are controlling the Torque in each Joint of the robot in order that the angle coordinates of each link coincide with the desired values. The proposed algorithm and robot model are built on Matlab-Simulink to investigate the system quality. The results show that the quality of the control system is very high: the response angles of each link quickly reach the desired values, and the static error equal to zero. [ABSTRACT FROM AUTHOR]

This work proposes an invariant descriptor and a pipeline for the registration of surface range images based on segmentation/reconstruction making use of an edge detection technique combined with a clustering technique using mesh decimation. This novel descriptor is applied to contours and it is invariant to similarity transformations including rotation, translation, uniform scale and it is robust to noise. The proposed feature descriptor makes use of corresponding points extracted from two images and a signature label is assigned specifically to a point considering the geometrical distribution of its neighbourhood, reducing possible areas of overlapping and the ambiguity in the search process. The descriptor was evaluated through a series of tests with various object range images. To validate the candidate transformations, the fitting errors between the two range images are evaluated by the iterative closest point algorithm. This study also presents and discusses results from the application of the developed pipeline in a vision sensor mounted on a robot arm specially built as part of a R&D project to acquire range images by laser scanning over the surface of hydraulic turbine blades. The sensor generates 3D surface models to be registered in the 3D coordinate system of the robot controller. [ABSTRACT FROM AUTHOR]

The development of an algorithm to describe a dynamic system and to predict its future behaviour in further consequence is the aim of the present study. Non parametric models provide a general description of object dynamics and artificial neural networks (ANN), which are a very flexible and universal learning method, belong to it. However, the standard estimation procedures for ANN like Levenberg-Marquardt (LM) do not consider that data is observed and consequently is uncertain. The combination with the extended Kalman filter (EKF) enables the consideration of the uncertainty in the estimation process. The analogies between EKF and LM are discussed and thereon the advantages of the EKF are outlined. The integration of ANN into EKF will be evaluated on an industrial robot arm. At first, a simplified model is determined; the ANN describes the robot position deviations as a function of the joint encoder values. The robot reference positions are measured by a laser tracker. In order to compare it with the robot outputs, the observations need to be transformed to the robot frame and the offset between the end-effector and the robot flange has to be determined. A method to estimate both parameters simultaneously is developed and the results are verified on basis of simulated data. This paper comprises two novel approaches. First, uncertainty is considered in the ANN estimation on basis of the combination with the EKF. Considering the full covariance matrix of the robot deviations leads to a better prediction of the robot's behaviour. Second, an integrated transformation and lever arm determination is introduced and the robot's repeatability presents the limiting factor of the achievable parameter uncertainty. [ABSTRACT FROM AUTHOR]

Carbon fiber-reinforced polymers (CFRPs) are of interest to the aerospace sector for meeting future CO2 emission targets due to their weight reduction potential. However, the detection of structural and matrix defects is crucial for determining the performance and suitability of CFRPs in current and future generations of aircraft. Computed laminography (CL), a well-established nondestructive testing method, is well suited to the scanning of CFRP components with large aspect ratios, for which the conventional computed tomography (CT) is less suitable. Utilizing an existing Nikon Metrology custom build X-ray CT scanner, two lift-in lift-out robotic sample manipulator systems are used to extend the capability of the system and allow the exploration of atypical scanning geometries. Implementing raster and limited angle trajectories, reconstructions using the ASTRA Tomography Toolbox and the Simultaneous Iterative Reconstruction Technique algorithm are able to show structural defects in CFRPs, despite the reduced information inherent with CL systems. This paper reports on the system design and initial experiments that demonstrate benefits and drawbacks of different design options and scanning trajectory choices. [ABSTRACT FROM AUTHOR]

The robot's arm trajectory can be used to improve the quality of the robot work. The current method utilizes the searching ability of the Alopex algorithm to perform a rough search of the robot's path of action to achieve the trajectory planning of its arm, but the planning efficiency is low. To this end, this paper uses chaos control to plan the robot arm trajectory. Based on the description of the robot arm trajectory planning, the robotic arm trajectory planning is completed by using the obstacle to the intersection time, probability prediction, motion planning strategy and real-time obstacle avoidance. Experiments show that this method can carry on the efficient planning to the robot arm trajectory. [ABSTRACT FROM AUTHOR]

A machine vision system for the automatic classification process is developed under different lighting environments, and has been applied to the operation of a robot arm with 6 degrees of freedom (DOF). In order to obtain accurate positioning information, the overall image is captured by a CMOS camera which is mounted above the working platform. The effects of back-lighting and front-lighting environments to the proposed system were investigated. With the front-lighting environment, four different conditions were performed. For each condition, global and local contrast threshold operations were used to obtain good image quality. In this study, a quadratic transformation used to describe the relationship between the image coordinates and the world coordinates was proposed, which has been compared to linear transformation as well as the camera calibration model in MATLAB tool. Experimental results show that in a back-lighting environment, the image quality is improved, such that the positions of the centers of objects are more accurate than in a front-lighting environment. According to the calibration results, the quadratic transformation is more accurate than other methods. By calculating the calibration deviation using the quadratic transformation, the maximum positive deviation is 0.48 mm and 0.38 mm in the X and Y directions, respectively. The maximum negative deviation is − 0.34 mm and − 0.43 mm in X and Y directions, respectively. The proposed system is effective, robust, and can be valuable to industry, as it offers an automated robotic system with an improved flexibility for separating dissimilar items of nominal value, in order to reclaim material investments, and decrease the expense of purchasing the same items again. [ABSTRACT FROM AUTHOR]

The contribution of biarticular muscles to the control of robotic arms and legs has recently attracted great interest in the field of robotics. The advantages of using biarticular muscles under kinetic interaction with the external environment have been well studied; however, the contribution of the muscles to the motion control of articulated robot arms under no kinetic interaction appears to remain an unclear issue, especially for robot arms of which the muscles are directly anchored to their links, which induces a change in the moment arms to allow the muscles to generate joint torques and permit point-to-point motion control to their desired postures in a feedforward manner with constant muscular forces. This paper presents a case study in which the role of biarticular muscles in the motion control of an articulated robot arm was investigated, focusing on the feature of its redundancy actuation, which allows an arbitrary choice from infinite combinations of muscular forces, realizing motion control to a desired posture. The numerical analysis in this paper addresses three typical combination choices. Mappings frommuscular forces to desired postures are calculated in the analysis of the three choices. The simulation results of motion control executed according to the three mappings are also analyzed. The analysis indicates the interesting results that biarticular muscles do not contribute to the desired postures and that a very weak dependence property of monoarticular muscles on the desired postures exists for a particular choice. The simulation results also demonstrate that the implementation of one choice results in a degraded motion control performance as compared with that of the two other choices. [ABSTRACT FROM AUTHOR]

In this paper, a robust nonlinear tracking control design for a bio-inspired robot arm with human-like motion mechanism is investigated, and the bio-inspired operator controller based on human multi-joint viscoelastic properties is designed by using operatorbased robust right coprime factorization approach. The motion mechanism of human multi-joint arm is used, and the measurement uncertainties of human multi-joint arm viscoelasticity are considered in designing bio-inspired operator controller. Based on the proposed design scheme, the sufficient conditions for the robust stability are derived in considering the coupling effects and measurement uncertainties, and the output tracking performance is realized. The effectiveness of the proposed design scheme was confirmed by the simulation results based on experimental data, and the time-varying estimated experimental data of human multi-joint arm viscoelasticity is used in simulation. [ABSTRACT FROM AUTHOR]

The integration of 3D concrete printing (3DCP) technology offers infinite possibilities and a wider palette of geometries for traditional concrete materials. This paper presents a pipeline for 3DCP by optimizing the material used in an irregularly shaped PETG formwork to ensure sufficient stiffness under dynamic loading conditions, while reducing the supporting equipment and costs in the manufacturing industry. The developed framework was validated through a case study that fabricated a concrete wall using a six-axis industrial robotic arm with a custom 3D printing system and parametric design modeling. Comprehensive failure analysis and numerical prediction performance were conducted to validate the proposed pipeline's viability. The formwork reinforcement process encourages smart manufacturing automation and customization, improving production precision. The presented insights offer exciting challenges and inspiration for future manufacturing industries. • Procedures introduced to fabricate large-scale irregular-shaped concrete architecture. • Optimization via genetic algorithm to suggest cost-effective structures. • Comprehensive experimentation to evaluate the robustness of 3D printed formwork. [ABSTRACT FROM AUTHOR]