Six-axis Robot Manipulator Research Articles

Calibration of rotary axis angular positioning deviations in a six-axis robotic manipulator by using the R-Test

Prediction accuracy of the kinematic model plays a pivotal role in offline numerical compensation for three-dimensional (3D) positioning error of a six-axis robotic manipulator. In addition to the Denavit-Hartenberg (D-H) error that was typically discussed in the analogous research, this paper proposes a novel scheme to identify the bidirectional angular positioning deviations of all the rotary axes without using the commercial laser tracker. This proposed scheme employs the R-Test, which is significantly more cost-efficient than a laser tracker employed in many past works. Compared to the conventional D-H model, significantly improved prediction performance of the proposed model was experimentally investigated on three rectangular paths covering the entire workspace. Experimental results indicate that the proposed scheme reduces the residual error from 505.2 to 215.2 mm, compared to 118.8 mm with a laser tracker, while maintaining a significantly lower cost that is 1/100 of a commercial laser tracker. Uncertainty analysis also clarify that when only the D-H error parameters are identified, as in many conventional works, the angular positioning deviations can be a major uncertainty contributor to the identification of the D-H errors. The proposed scheme does not require the R-Test locations to be calibrated, and its influence on the uncertainty in the identified errors is assessed.

Sequential Optimal Trajectory Planning Scheme for Robotic Manipulators along Specified Path Based on Direct Collocation Method

Robotic manipulators play a pivotal role in modern intelligent manufacturing and unmanned production systems, often tasked with executing specific paths accurately. However, the input of the robotic manipulators is trajectory which is a path with time information. The resulting core technology is trajectory planning methods which are broadly classified into two categories: maximum velocity curve (MVC) methods and multiphase direct collocation (MPDC) methods. This paper concentrates on addressing challenges associated with the latter methods. In MPDC methods, the solving efficiency and accuracy are greatly influenced by the number of discretization nodes. When dealing with systems with complex dynamics, such as robotic manipulators, striking a balance between solving time and path discretization errors becomes crucial. We use a mesh refinement (MR) algorithm to find a suitable number of nodes under the premise of ensuring the path discretization error. So, the actual device can effectively implement the planned solutions. Nonetheless, the conventional application of the MR algorithm requires solving the original problem in each iteration; these processes are extremely time-consuming and may fail to solve when dealing with a complex dynamic system. As a result, we propose a sequential optimal trajectory planning scheme to solve the problem efficiently by dividing the original optimal control (OC) problem into two stages: path planning (PP) and trajectory planning (TP). In the PP stage, we employ a DC method based on arc length and an MR algorithm to identify key nodes along the specified path. This aims to minimize the approximation error introduced during discretization. In the TP stage, the identified key nodes serve as boundary conditions for an MPDC method based on time. This facilitates the generation of an optimal trajectory that maximizes motion performance, considering constant velocity in Cartesian space and dynamic constraints while keeping the path discretization error. Simulation and experiment are conducted with a six-axis robotic manipulator, ROCR6, and show significant potential for a wide range of applications in robotics.

Influence of rotary axis angular positioning error motions on robotic probing

The accuracy of touch-trigger probing by a six-axis robotic manipulator is determined by the accuracy of the robot forward kinematic model to estimate the stylus sphere position from angular positions of rotary axes. Many conventional studies have employed the Denavit–Hartenberg (DH) model, containing position and orientation errors of the rotary axis average lines as error sources. This paper proposes the application of a new kinematic model, containing the angular positioning deviations of all the rotary axes, to the robotic probing. The probing accuracy is experimentally investigated in profile probing of a straightedge over the robot's workspace.

Application of a mathematical model for the Motoman MH-50 industrial robot’s electric drive system

<p>In recent years, there has been a great interest in the transition to digital and automation services for dangerous and menial working processes. Due to its MH50-35 industrial robot, Motoman's properties allow us to improve the control system of an electric drive for industrial robots. The structure of the electric drive for six-axis robot manipulator performance can be superior to conventional Drive Control servos for motor excitation, and a novel automation system can be implemented for its servo performance. To solve these issues, we propose an optimization strategy that allows us to achieve an increase in productivity and labor safety in the industry, reduce the percentage of defects, guarantee product uniformity, and reduce the prime cost of production of items. Ideal conditions were anticipated using a mathematical model. In this study, by using a statistical model, the ideal conditions were synthesized. The optimization of the control system of an electric drive for industrial robot analysis was carried out, and our findings suggest using this model in industrial production to elucidate problems such as high accuracy and speed indicators.</p>

Novel and Efficient Methodology for Drop Placement Accuracy Testing of Robot-Guided Inkjet Printing onto 3D Objects

Robot-guided inkjet printing technology offers a new way for the digital and additive deposition of low-viscous inks to be made directly onto arbitrary surfaces and, thus, enables the production of individualized printed electronics on large-scale objects. When compared to conventional flatbed printing, the distance between the nozzle plate and the object’s surface varies and needs to be considered in order to match the accuracy requirements needed for the positioning of single drops. Knowledge about applicable distance limits and the influence of tunable print parameters is crucial for improving the print process and results. This study discusses the sources of errors in the inkjet printing process onto 3D objects and presents extensive results about position accuracy in relation to jetting distance for different parameter sets of functional inks, drop volumes, and piezo voltages. Additionally, an efficient novel method was applied to determine the drop position accuracy of inkjet droplets in relation to the jetting distance. The method relies on cylinder geometry for the object and an inkjet head that is guided by a six-axis robot manipulator along the cylinder’s axis. For the determination of drop placement accuracy, the position of single dots on the surface was compared to a model which considered the cylinder radii, drop velocity, and the movement speed of the guided inkjet printhead. The method and the extensive research results can be utilized for the prediction of achievable drop placement accuracy and the prior definition of distance limits.

A Neural Network Based Approach to Inverse Kinematics Problem for General Six-Axis Robots.

Inverse kinematics problems (IKP) are ubiquitous in robotics for improved robot control in widespread applications. However, the high non-linearity, complexity, and equation coupling of a general six-axis robotic manipulator pose substantial challenges in solving the IKP precisely and efficiently. To address this issue, we propose a novel approach based on neural network (NN) with numerical error minimization in this paper. Within our framework, the complexity of IKP is first simplified by a strategy called joint space segmentation, with respective training data generated by forward kinematics. Afterwards, a set of multilayer perception networks (MLP) are established to learn from the foregoing data in order to fit the goal function piecewise. To reduce the computational cost of the inference process, a set of classification models is trained to determine the appropriate forgoing MLPs for predictions given a specific input. After the initial solution is sought, being improved with a prediction error minimized, the refined solution is finally achieved. The proposed methodology is validated via simulations on Xarm6-a general 6 degrees of freedom manipulator. Results further verify the feasibility of NN for IKP in general cases, even with a high-precision requirement. The proposed algorithm has showcased enhanced efficiency and accuracy compared to NN-based approaches reported in the literature.

Fine Alignment of Thermographic Images for Robotic Inspection of Parts with Complex Geometries.

Increasing the efficiency of the quality control phase in industrial production lines through automation is a rapidly growing trend. In non-destructive testing, active thermography techniques are known for their suitability to allow rapid non-contact and full-field inspections. The robotic manipulation of the thermographic instrumentation enables the possibility of performing inspections of large components with complex geometries by collecting multiple thermographic images from optimal positions. The robotisation of the thermographic inspection is highly desirable to improve assessment speed and repeatability without compromising inspection accuracy. Although integrating a robotic setup for thermographic data capture is not challenging, the application of robotic thermography has not grown significantly to date due to the absence of a suitable approach for merging multiple thermographic images into a single presentation. Indeed, such an approach must guarantee accurate alignment and consistent pixel blending, which is crucial to facilitate defect detection and sizing. In this work, an innovative inspection platform was conceptualised and implemented, consisting of a pulsed thermography setup, a six-axis robotic manipulator and an algorithm for image alignment, correction and blending. The performance of the inspection platform is tested on a convex-shaped specimen with artificial defects, which highlights the potential of the new combined approach. This work bridges a technology gap, making thermographic inspections more deployable in industrial environments. The proposed fine image alignment approach can find applicability beyond thermographic non-destructive testing.

Laser Direct-Write Sensors on Carbon-Fiber-Reinforced Poly-Ether-Ether-Ketone for Smart Orthopedic Implants.

Mechanically close‐to‐bone carbon‐fiber‐reinforced poly‐ether–ether–ketone (CFR‐PEEK)‐based orthopedic implants are rising to compete with metal implants, due to their X‐ray transparency, superior biocompatibility, and body‐environment stability. While real‐time strain assessment of implants is crucial for the postsurgery study of fracture union and failure of prostheses, integrating precise and durable sensors on orthopedic implants remains a great challenge. Herein, a laser direct‐write technique is presented to pattern conductive features (minimum sheet resistance <1.7 Ω sq–1) on CRF‐PEEK‐based parts, which can act as strain sensors. The as‐fabricated sensors exhibit excellent linearity (R 2 = 0.997) over the working range (0–2.5% strain). While rigid silicon‐ or metal‐based sensor chips have to be packaged onto flat surfaces, all‐carbon‐based sensors can be written on the complex curved surfaces of CFR‐PEEK joints using a portable laser mounted on a six‐axis robotic manipulator. A wireless transmission prototype is also demonstrated using a Bluetooth module. Such results will allow a wider space to design sensors (and arrays) for detailed loading progressing monitoring and personalized diagnostic applications.

Experimental implementation of the laser shock peening method aimed at an increase in the fatigue properties of metals

The study is aimed at the development and implementation of an experimental setup for treating metal parts with complex geometry to induce compressive residual stresses in the surface layers. Modern methods of surface treatment demonstrated the possibility of increasing the durability of parts by several times through creation of high-amplitude residual compressive stresses. We managed to form the residual compressive stresses up to a depth of 1 mm using the titanium alloy specimens. The developed installation consists of a solid-state laser with a pulse energy of up to 10 J, a six-axis robot manipulator, and a system for measuring residual stresses by hole drilling method. The processing is realized in automatic mode with the possibility of continuous change of specimens. The geometry of parts and processing features are worked out on a digital three-dimensional model of the part. A number of tests have been carried out to reveal the dependence of the values of residual stresses on the processing conditions and demonstrate the necessity of numerical analysis and preliminary modeling of the process of laser shock peening. The distribution of residual stresses was measured by hole drilling method in the specimens before and after laser shock peening under various processing conditions, and the profiles of these stresses in depth were plotted. It is shown that along with the pulse power, the value and distribution of residual stresses are significantly affected by the number of repeated passes, the overlap degree, and the technology of preliminary preparation of the specimen surface. The analysis made it possible to choose the optimal processing mode for titanium alloys providing the values of residual compressive stresses up to 1 GPa.

Research on obstacle avoidance method of robot manipulator based on binocular vision

Aiming at static obstacles in indoor environment, the six-axis robot manipulator can avoid obstacles successfully through binocular stereo vision system. According to the principle of camera imaging, the camera calibration is completed by using the camera calibration toolbox of MATLAB, and then the three-dimensional coordinates of the feature points of obstacles are obtained by using the Structure from Motion (SFM) algorithm, so as to determine the location of obstacles. In the aspect of path planning, combining the characteristics of binocular visual obstacle recognition, the artificial potential field (APF) method is used to realize the obstacle avoidance. Finally, the simulation and data analysis under the Matlab development environment verify the feasibility of the algorithm in the binocular vision obstacle avoidance system.

In-situ construction method for lunar habitation: Chinese Super Mason

Abstract Lunar exploration has become increasingly popular, and lunar habitation research must be a core focus during the exploration of the Moon. The lunar habitation research must mainly include architectural and structural designs built using suitable material-forming technology and construction equipment. To address these issues, Chinese Super Mason (CSM) was proposed. This technology is an autonomous robotic construction system that is capable of automated assembling on-site prefabricated multistructural bricks and arched segments. The compound fabrication system was composed of a six-axis robotic manipulator and a dry mixed autoclaving fabricator carried on an autonomous-limbed vehicle platform. The Xuanwu Station for the lunar habitation conceptual design was developed and intended for erection by the CSM. A case study was conducted in a 2.8 m-long, 0.8 m-wide, and 1.1 m-high open arched-formwork structure fabricated within 8.5 h on the Earth. In addition, the Xuanwu Station was evaluated using finite element analysis software considering the temperature, air pressure, and other special environments on the Moon. The reliabilities and limitations of the CSM method were analyzed. Finally, the applications of the CSM in the extreme environment of the Earth and several improvements of the experimental equipment were discussed along with the proposed future applications for autonomous construction.

Study of Industrial Robot Numerical Control Program Based on Stationary Tool Control

Six-axis robotic manipulators continue to play a vital role in the development of industrial automation worldwide. Mechanical arms incorporated with computer-aided design and manufacturing systems have gradually received attention in the field of manufacturing. This study adopted the Denavit-Hartenberg notation to construct a kinematic model of the FANUC M-20iA/20M six-axis robot manipulator configuration with stationary point control. Visual C# was employed to develop the transformation interface which converts the tool path files generated from Unigraphics NX software into readable robotic manipulator formats. This study adopted FANUC ROBOGUIDE simulation software for further verification and comparison. The results validate the proposed scheme.

3D Perception-Based Collision-Free Robotic Leaf Probing for Automated Indoor Plant Phenotyping

Abstract. Various instrumentation devices for plant physiology studies, such as spectrometers, chlorophyll fluorometers, and Raman spectroscopy sensors, require accurate placement of their sensor probes toward the leaf surface to meet specific requirements of probe-to-target distance and orientation. In this work, a Kinect V2 sensor, a high-precision 2D laser profilometer, and a six-axis robotic manipulator were used to automate the leaf probing task. The relatively wide field of view and high resolution of the Kinect V2 allowed rapid capture of the full 3D environment in front of the robot. The location and size of each plant were estimated by k-means clustering where k was the user-defined number of plants. A real-time collision-free motion planning framework based on probabilistic roadmaps was adapted to maneuver the robotic manipulator without colliding with the plants. Each plant was scanned from the top with the short-range profilometer to obtain high-precision 3D point cloud data. Potential leaf clusters were extracted by a 3D region growing segmentation scheme. Each leaf segment was further partitioned into small patches by a voxel cloud connectivity segmentation method. Only the patches with low root mean square errors of plane fitting were used to compute leaf probing poses of the robot. Experiments conducted inside a growth chamber mockup showed that the developed robotic leaf probing system achieved an average motion planning time of 0.4 s with an average end-effector travel distance of 1.0 m. To examine the probing accuracy, a square surface was scanned at different angles, and its centroid was probed perpendicularly. The average absolute probing errors of distance and angle were 1.5 mm and 0.84°, respectively. These results demonstrate the utility of the proposed robotic leaf probing system for automated non-contact deployment of spectroscopic sensor probes for indoor plant phenotyping under controlled environmental conditions. Keywords: 3D perception, Agricultural robotics, Leaf probing, Motion planning, Plant phenotyping.

Six-axis Robot Manipulator Numerical Control Programming and Motion Simulation

This study, using the KUKA KR 150-2 six-axis robot manipulator configuration, adopted the Denavit-Hartenberg notation to build relevant kinematic mathematical model so that subsequent forward and inverse kinematics could be derived. Borland C++ Builder was employed to program the simulation interface, transforming the tool path files generated from hyperMILL CAD/CAM software into readable formats by robot manipulators. Moreover, OpenGL was used to complete the kinematic simulation of robot manipulators. Finally, this study adopted the solid cutting simulation software VERICUTÃ’ for further verification and comparison. Result indicates the effectiveness of the proposed scheme.

Field programmable gate array–based servo control integrated chip for a six-axis articulated robot manipulator

The objective of this article is to build a field programmable gate array–based six-axis servo control integrated chip which can integrate the function of a motion trajectory planning and the function of six position/speed/current servo controllers into one integrated chip. In the work, first, a mathematical modeling of a robot manipulator with the actuator using permanent magnet synchronous motor is derived. Second, the proportional controller in the position loop, a proportional–integral controller in the speed loop and a vector controller in the current loop for each axis are applied. Third, a system on a programmable chip) technology which comprises an Altera field programmable gate array chip and an embedded soft-core Nios-II processor is considered to develop the proposed servo control integrated chip. However, in the servo control integrated chip, it has two modules. The first module is an embedded soft-core Nios-II processor which is used to generate the motion trajectory planning by software. The second module presents a six-axis servo controller intellectual property by hardware which is applied to execute six position/speed/current controllers. Therefore, the function of a motion trajectory command and the function of six position/speed/current servo controllers for a six-axis robot manipulator can be integrated into one field programmable gate array. Finally, to verify the effectiveness and correctness of the proposed field programmable gate array–based servo control integrated chip, a six-axis robot manipulator is applied and some experimental results are demonstrated.

From Need to Innovation [Industrial Activities

Reports on JACO, the robotic manipulator. Launched in 2010, JACO is a six-axis robotic manipulator arm with a three-fingered hand. This little marvel of engineering significantly improves the lives of persons with reduced mobility. Lightweight, very quiet, unobtrusive, safe, and even weatherproof, JACO assists anyone with an upper-body mobility impairment.

Universal six-joint robot controller

The authors describe the specifications, design, and implementation of a general-purpose six-axis robotic manipulator controller developed to serve as a research tool for investigating practical and theoretical aspects of control strategies in robotics. The 80286-based Intel System 310 was used for running the XENIX operating servo software as well as higher-level software that implements kinematics and path planning. A multibus-compatible interface board was designed and constructed to handle input/output signals from the joint motors of the robot manipulator. The universal controller is capable of driving robot manipulators equipped with electric joint motors and position optical encoders. To test functionality, the controller was connected to the joint motor DC power amplifier of a Unimate PUMA 560 arm, bypassing completely the manufacturer-supplied Unimation controller; proportional-integral-derivative (PID) control laws were installed into the XENIX operating system. Additional software drivers were implemented to allow application programs access to the interface board. All software was written in the C language. >