A fixed-distance planning algorithm for 6-DOF manipulators

2015 ◽  
Vol 42 (6) ◽  
pp. 586-599 ◽  
Author(s):  
Mingyu Gao ◽  
Da Chen ◽  
Yuxiang Yang ◽  
Zhiwei He
Keyword(s):  
Trajectory Planning ◽  
Degrees Of Freedom ◽  
Position Control ◽  
Control Strategies ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Cartesian Coordinates ◽  
Content Type ◽  
Fixed Distance ◽  
Planning Algorithm

Purpose – The purpose of this paper is to propose a new trajectory planning algorithm for industrial robots, which can let the robots move through a desired spatial trajectory, avoid colliding with other objects and achieve accurate movements. Trajectory planning algorithms are the soul of motion control of industrial robots. A predefined space trajectory can let the robot move through the desired spatial coordinates, avoid colliding with other objects and achieve accurate movements. Design/methodology/approach – The mathematical expressions of the proposed algorithm are deduced. The speed control, position control and orientation control strategies are realized and verified with simulations, and then implemented on a six degrees of freedom (6-DOF) industrial robot platform. Findings – A fixed-distance trajectory planning algorithm based on Cartesian coordinates was presented. The linear trajectory, circular trajectory, helical trajectory and parabolic trajectory in Cartesian coordinates were implemented on the 6-DOF industrial robot. Originality/value – A simple and efficient algorithm is proposed. Enrich the kind of trajectory which the industrial robot can realize. In addition, the industrial robot can move more concisely, smoothly and precisely.

Validation of Minimum Time-Jerk Algorithms for Trajectory Planning of Industrial Robots

2011 ◽  
Vol 3 (3) ◽  
Author(s):  
A. Gasparetto ◽  
A. Lanzutti ◽  
R. Vidoni ◽  
V. Zanotto
Keyword(s):  
Dynamic Model ◽  
Trajectory Planning ◽  
Experimental Analysis ◽  
Execution Time ◽  
Industrial Robot ◽  
Experimental Tests ◽  
Industrial Robots ◽  
Minimum Time ◽  
Mechanical Constraints ◽  
Planning Algorithm

In this paper, an experimental analysis and validation of a minimum time-jerk trajectory planning algorithm is presented. The technique considers both the execution time and the integral of the squared jerk along the whole trajectory, so as to take into account the need for fast execution and the need for a smooth trajectory, by adjusting the values of two weights. The experimental tests have been carried out by using an accelerometer mounted on a Cartesian robot. The algorithm does not require a dynamic model of the robot, but just its mechanical constraints, and can be implemented in any industrial robot. The outcomes of the tests have been compared with both simulation and experimental results yielded by two trajectory planning algorithms taken from the literature.

scholarly journals Research on Trajectory Planning of Six Degrees of Freedom Robot

2019 ◽  
Vol 25 ◽  
pp. 01010
Author(s):  
Hao Zhou
Keyword(s):  
Trajectory Planning ◽  
Degrees Of Freedom ◽  
Simulation Analysis ◽  
Industrial Robot ◽  
Research Direction ◽  
Industrial Robots ◽  
Degree Of Freedom ◽  
Continuous Development ◽  
Six Degrees Of Freedom ◽  
Six Degree Of Freedom

With the continuous development of industrial automation, the demand for industrial robots in the manufacturing field is gradually increasing. In order to meet the needs of different occasions and functions, the planning of the trajectory of the robot becomes the research direction of the six-degree-of-freedom robot. The research object of this paper is a six-degree-of-freedom industrial robot. According to engineering needs, a structure of a handling robot is designed. The kinematics of the robot and its trajectory planning are studied, and the simulation analysis is made.

Precision Evaluation of NeXus, a Custom Multi-Robot System for Microsystem Integration

2021 ◽  
Author(s):  
Danming Wei ◽  
Alireza Tofangchi ◽  
Andriy Sherehiy ◽  
Mohammad Hossein Saadatzi ◽  
Moath Alqatamin ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
Industrial Robot ◽  
Sensor Arrays ◽  
Industrial Robots ◽  
Element Analysis ◽  
Product Packaging ◽  
Precision Evaluation ◽  
High Efficient ◽  
Supporting Frame ◽  
Microsystem Integration

Abstract Industrial robots, as mature and high-efficient equipment, have been applied to various fields, such as vehicle manufacturing, product packaging, painting, welding, and medical surgery. Most industrial robots are only operating in their own workspace, in other words, they are floor-mounted at the fixed locations. Just some industrial robots are wall-mounted on one linear rail based on the applications. Sometimes, industrial robots are ceiling-mounted on an X-Y gantry to perform upside-down manipulation tasks. The main objective of this paper is to describe the NeXus, a custom robotic system that has been designed for precision microsystem integration tasks with such a gantry. The system tasks include assembly, bonding, and 3D printing of sensor arrays, solar cells, and microrobotic prototypes. The NeXus consists of a custom designed frame, providing structural rigidity, a large overhead X-Y gantry carrying a 6 degrees of freedom industrial robot, and several other precision positioners and processes. We focus here on the design and precision evaluation of the overhead ceiling-mounted industrial robot of NeXus and its supporting frame. We first simulated the behavior of the frame using Finite Element Analysis (FEA), then experimentally evaluated the pose repeatability of the robot end-effector using three different types of sensors. Results verify that the performance objectives of the design are achieved.

Energy consumption optimization for AC drives position control

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Branislav Ftorek ◽  
Milan Saga ◽  
Pavol Orsansky ◽  
Jan Vittek ◽  
Peter Butko
Keyword(s):  
Control System ◽  
Energy Saving ◽  
Energy Savings ◽  
Position Control ◽  
Control Strategies ◽  
Content Type ◽  
Ac Drives ◽  
Energy Demands ◽  
Wide Range ◽  
Energy Consumption Optimization

Purpose The main purpose of this paper is to evaluate the two energy saving position control strategies for AC drives valid for a wide range of boundary conditions including an analysis of their energy expenses. Design/methodology/approach For energy demands analysis, the optimal energy control based on mechanical and electrical losses minimization is compared with the near-optimal one based on symmetrical trapezoidal speed profile. Both control strategies respect prescribed maneuver time and define acceleration profile for preplanned rest-to-rest maneuver. Findings Presented simulations confirm lower total energy expenditures of energy optimal control if compared with near-optimal one, but the differences are only small due to the fact that two energy saving strategies are compared. Research limitations/implications Developed overall control system consisting of energy saving profile generator, pre-compensator and position control system respecting principles of field-oriented control is capable to track precomputed state variables precisely. Practical implications Energy demands of both control strategies are verified and compared to simulations and preliminary experiments. The possibilities of energy savings were confirmed for both control strategies. Originality/value Experimental verification of designed control structure is sufficiently promising and confirmed assumed energy savings.

Optimization design of drive system for industrial robots based on dynamic performance

2017 ◽  
Vol 44 (6) ◽  
pp. 765-775 ◽  
Author(s):  
LianZheng Ge ◽  
Jian Chen ◽  
Ruifeng Li ◽  
Peidong Liang
Keyword(s):  
Optimization Model ◽  
Optimization Problem ◽  
Industrial Robot ◽  
Dynamic Performance ◽  
System Optimization ◽  
Drive System ◽  
Industrial Robots ◽  
Mixed Integer ◽  
Light Weight ◽  
Content Type

Purpose The global performance of industrial robots partly depends on the properties of drive system consisting of motor inertia, gearbox inertia, etc. This paper aims to deal with the problem of optimization of global dynamic performance for robotic drive system selected from available components. Design/methodology/approach Considering the performance specifications of drive system, an optimization model whose objective function is composed of working efficiency and natural frequency of robots is proposed. Meanwhile, constraints including the rated and peak torque of motor, lifetime of gearbox and light-weight were taken into account. Furthermore, the mapping relationship between discrete optimal design variables and component properties of drive system were presented. The optimization problem with mixed integer variables was solved by a mixed integer-laplace crossover power mutation algorithm. Findings The optimization results show that our optimization model and methods are applicable, and the performances are also greatly promoted without sacrificing any constraints of drive system. Besides, the model fits the overall performance well with respect to light-weight ratio, safety, cost reduction and others. Practical implications The proposed drive system optimization method has been used for a 4-DOF palletizing robot, which has been largely manufactured in a factory. Originality/value This paper focuses on how the simulation-based optimization can be used for the purpose of generating trade-offs between cost, performance and lifetime when designing robotic drive system. An applicable optimization model and method are proposed to handle the dynamic performance optimization problem of a drive system for industrial robot.

scholarly journals A new joint friction model for parameter identification and sensor-less hand guiding in industrial robots

2020 ◽  
Vol 47 (6) ◽  
pp. 847-857
Author(s):  
Guanghui Liu ◽  
Qiang Li ◽  
Lijin Fang ◽  
Bing Han ◽  
Hualiang Zhang
Keyword(s):  
Industrial Robot ◽  
Angular Displacement ◽  
Weighted Least Squares ◽  
Friction Model ◽  
Industrial Robots ◽  
Model Parameters ◽  
Dynamic Parameters ◽  
Content Type ◽  
Joint Friction ◽  
Six Dof

Purpose The purpose of this paper is to propose a new joint friction model, which can accurately model the real friction, especially in cases with sudden changes in the motion direction. The identification and sensor-less control algorithm are investigated to verify the validity of this model. Design/methodology/approach The proposed friction model is nonlinear and it considers the angular displacement and angular velocity of the joint as a secondary compensation for identification. In the present study, the authors design a pipeline – including a manually designed excitation trajectory, a weighted least squares algorithm for identifying the dynamic parameters and a hand guiding controller for the arm’s direct teaching. Findings Compared with the conventional joint friction model, the proposed method can effectively predict friction factors during the dynamic motion of the arm. Then friction parameters are quantitatively obtained and compared with the proposed friction model and the conventional friction model indirectly. It is found that the average root mean square error of predicted six joints in the proposed method decreases by more than 54%. The arm’s force control with the full torque using the estimated dynamic parameters is qualitatively studied. It is concluded that a light-weight industrial robot can be dragged smoothly by the hand guiding. Practical implications In the present study, a systematic pipeline is proposed for identifying and controlling an industrial arm. The whole procedure has been verified in a commercial six DOF industrial arm. Based on the conducted experiment, it is found that the proposed approach is more accurate in comparison with conventional methods. A hand-guiding demo also illustrates that the proposed approach can provide the industrial arm with the full torque compensation. This essential functionality is widely required in many industrial arms such as kinaesthetic teaching. Originality/value First, a new friction model is proposed. Based on this model, identifying the dynamic parameter is carried out to obtain a set of model parameters of an industrial arm. Finally, a smooth hand guiding control is demonstrated based on the proposed dynamic model.

A direct approach to solving trajectory planning problems using genetic algorithms with dynamics considerations in complex environments

Robotica ◽  
2014 ◽  
Vol 33 (3) ◽  
pp. 669-683 ◽  
Author(s):  
Fares J. Abu-Dakka ◽  
Francisco J. Valero ◽  
Jose Luis Suñer ◽  
Vicente Mata
Keyword(s):  
Trajectory Planning ◽  
Direct Method ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Computational Time ◽  
Planning Problem ◽  
Complex Environments ◽  
Operational Parameters ◽  
Algorithm Efficiency ◽  
Planning Problems

SUMMARYThis paper presents a new genetic algorithm methodology to solve the trajectory planning problem. This methodology can obtain smooth trajectories for industrial robots in complex environments using a direct method. The algorithm simultaneously creates a collision-free trajectory between initial and final configurations as the robot moves. The presented method deals with the uncertainties associated with the unknown kinematic properties of intermediate via points since they are generated as the algorithm evolves looking for the solution. Additionally, the objective of this algorithm is to minimize the trajectory time, which guides the robot motion. The method has been applied successfully to the PUMA 560 robotic system. Four operational parameters (execution time, computational time, end-effector distance traveled, and significant points distance traveled) have been computed to study and analyze the algorithm efficiency. The experimental results show that the proposed optimization algorithm for the trajectory planning problem of an industrial robot is feasible.

scholarly journals ABB IRB 120-30.6 Build Procedure in RoboDK

2021 ◽  
pp. 256-264
Author(s):  
Sudip Chakraborty ◽  
P. S. Aithal
Keyword(s):  
Design Methodology ◽  
Degrees Of Freedom ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Research Purpose ◽  
Six Degrees Of Freedom ◽  
Simulation Based ◽  
Software Download ◽  
Coordinate Assignment

Purpose: Research on robotics needs a robot to experiment on it. The actual industrial robot is costly. So, the only resort is to use a Robot simulator. The RoboDK is one of the best robot simulators now. It has covered most of the popular industrial robots. Its interface is straightforward. Just open the software, download the robot as we need, and start experiments. Up to that, no issue was found anywhere. However, the problem begins when we want to build the simulated robot by own. Lots of complexity arises like coordinate assignment, rotation not aligned, length mismatch, robot not synced with DH parameter. We begin to find some documents for making the robots. A few bits of the document are present. That is why we research it. After doing that, we prepared this paper for the researcher who wants to develop the simulated robot independently. This paper can be referenced for them. To minimize the complexity of our research, we study an industrial robot, ABB IRB 120-30.6. It is a good and popular robot. It is six degrees of freedom robot. We will use the specification and STEP file from their respective website and build a simulated robot from the STEP file for our research purpose. Design/Methodology/Approach: We will create a simulated robot from ABB IRB 120-30.6 STEP file. To create a robot by own, we took the help of the IRB 120 robot model. To demonstrate as simple as possible, we start with that robot whose default design is already present. We match and tune the joint coordinate based on robot parameters through this experiment. Findings/results: Here, we see how to create a custom robot. Using the IRB 120 robot model, we will create a robot model step by step. Furthermore, it will move it around its axis. Originality/Value: Using this experiment, the new researcher can get valuable information to create their custom robot. Paper Type: Simulation-based Research.

scholarly journals Design of an Accurate and Stiff Wooden Industrial Robot: First Steps Toward Robot Eco-sustainable Mechanical Design

2020 ◽  
Vol 12 (5) ◽  
Author(s):  
Sébastien Briot ◽  
Lila Kaci ◽  
Clément Boudaud ◽  
David Llevat Pamiès ◽  
Pauline Lafoux ◽  
...  
Keyword(s):  
Design Process ◽  
Mechanical Design ◽  
Control Strategies ◽  
Industrial Robot ◽  
Integrated Design ◽  
Industrial Robots ◽  
Stiffness Ratio ◽  
Robot Accuracy ◽  
Integrated Design Process ◽  
Accuracy Performance

Abstract This article investigates the feasibility of replacing metal robot links by wooden bodies for eco-sustainable design’s purpose. Wood is a material with low environmental impact and a good mass-to-stiffness ratio. However, it has significant dimensional and mechanical variabilities. This is an issue for industrial robots that must be accurate and stiff. To guarantee stiffness and accuracy performance of a wooden robot, we propose an integrated design process combining (i) proper wood selection, (ii) adequate sensor-based control strategies to ensure robot accuracy, and (iii) a robust design approach dealing with wood uncertainties. Based on the use of this integrated design process, a prototype of a wooden five-bar mechanism is designed and manufactured. Experimental results show that it is realistic to design a wooden robot with performance compatible with industry requirements in terms of stiffness (deformations lower than 400 μm for 20 N loads) and accuracy (repeatability lower than 60 μm), guaranteed in a workspace of 800 mm × 200 mm. This study provides a first step toward the eco-sustainable mechanical design of robots.

Study of Neural-Kinematics Architectures for Model-Less Calibration of Industrial Robots

2021 ◽  
Vol 33 (1) ◽  
pp. 158-171
Author(s):  
Monica Tiboni ◽  
◽  
Giovanni Legnani ◽  
Nicola Pellegrini
Keyword(s):  
Degrees Of Freedom ◽  
Industrial Robot ◽  
Kinematic Model ◽  
Back Propagation ◽  
Simulated Data ◽  
Industrial Robots ◽  
Robot Calibration ◽  
Feed Forward Neural Network ◽  
Comparative Performance ◽  
Order Of Magnitude

Modeless industrial robot calibration plays an important role in the increasing employment of robots in industry. This approach allows to develop a procedure able to compensate the pose errors without complex parametric model. The paper presents a study aimed at comparing neural-kinematic (N-K) architectures for a modeless non-parametric robotic calibration. A multilayer perceptron feed-forward neural network, trained in a supervised manner with the back-propagation learning technique, is coupled in different modes with the ideal kinematic model of the robot. A comparative performance analysis of different neural-kinematic architectures was executed on a two degrees of freedom SCARA manipulator, for direct and inverse kinematics. Afterward the optimal schemes have been identified and further tested on a three degrees of freedom full SCARA robot and on a Stewart platform. The analysis on simulated data shows that the accuracy of the robot pose can be improved by an order of magnitude after compensation.

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