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 Maximizing the Coverage of Roadmap Graph for Optimal Motion Planning

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-23 ◽  
Author(s):  
Jae-Han Park ◽  
Tae-Woong Yoon
Keyword(s):  
Motion Planning ◽  
Industry 4.0 ◽  
Industrial Robot ◽  
Efficient Solutions ◽  
Industrial Robots ◽  
Optimal Motion ◽  
Optimal Motion Planning ◽  
Planning Problems ◽  
Complex Planning ◽  
Satisfactory Quality

Automated motion-planning technologies for industrial robots are critical for their application to Industry 4.0. Various sampling-based methods have been studied to generate the collision-free motion of articulated industrial robots. Such sampling-based methods provide efficient solutions to complex planning problems, but their limitations hinder the attainment of optimal results. This paper considers a method to obtain the optimal results in the roadmap algorithm that is representative of the sampling-based method. We define the coverage of a graph as a performance index of its optimality as constructed by a sampling-based algorithm and propose an optimization algorithm that can maximize graph coverage in the configuration space. The proposed method was applied to the model of an industrial robot, and the results of the simulation confirm that the roadmap graph obtained by the proposed algorithm can generate results of satisfactory quality in path-finding tests under various conditions.

A direct approach to modeling an industrial robot from samples of input-output data

Robotica ◽  
1984 ◽  
Vol 2 (3) ◽  
pp. 161-167 ◽  
Author(s):  
Ajit M. Karnik ◽  
Naresh K. Sinha
Keyword(s):  
Control Systems ◽  
Direct Method ◽  
Industrial Robot ◽  
Industrial Robots ◽  
Continuous Time Model ◽  
Output Data ◽  
Time Model ◽  
System A ◽  
Input And Output ◽  
A Direct Method

SUMMARYThe increased demand on the performance and efficiency of industrial robots, has led to the design of sophisticated control systems. Such control systems require an accurate dynamic model of the system. A commonly used method of modeling an industrial robot, involves the description of a set of dynamic equations, relating actuator torques to loads and accelerations. These equations are generally quite complex and inconvenient for implementation on digital computers.Another method often used for identification, is the ‘indirect method’, in which the transfer function is obtained in two steps. The discrete time model is first derived from samples of the input and output measurements, which is then transformed to the continuous-time model. A limitation of this method is that it requires the excitation to be of the ‘persistently exciting’ type, thus precluding the application of simple inputs like the step signal.This paper describes a ‘direct’ method for identification of an ‘industrial robot’ from samples of input and output observations. Results of modeling an industrial robot and two simulations are presented. One of the simulations, and the industrial robot uses the step input as excitation. The other example was excited with an exponential input.

scholarly journals Dynamic Simulation Modeling of Industrial Robot Kinematics in Industry 4.0

2022 ◽  
Vol 2022 ◽  
pp. 1-11
Author(s):  
Guang Jin ◽  
Shuai Ma ◽  
Zhenghui Li
Keyword(s):  
Dynamic Simulation ◽  
Trajectory Planning ◽  
Simulation Modeling ◽  
Industry 4.0 ◽  
Industrial Robot ◽  
Error Model ◽  
Position Error ◽  
Industrial Robots ◽  
Robot Kinematics ◽  
Kinetic Characteristics

This paper studies the kinematic dynamic simulation modeling of industrial robots in the Industry 4.0 environment and guides the kinematic dynamic simulation modeling of industrial robots in the Industry 4.0 environment in the context of the research. To address the problem that each parameter error has different degrees of influence on the end position error, a method is proposed to calculate the influence weight of each parameter error on the end position error based on the MD-H error model. The error model is established based on the MD-H method and the principle of differential transformation, and then the function of uniform variation of six joint angles with time t is constructed to ensure that each linkage geometric parameter is involved in the motion causing error accumulation. Through the analysis of the robot marking process, the inverse solution is optimized for multiple solutions, and a unique engineering solution is obtained. Linear interpolation, parabolic interpolation, polynomial interpolation, and spline curve interpolation are performed on the results after multisolution optimization in the joint angle, and the pros and cons of various interpolation results are analyzed. The trajectory planning and simulation of industrial robots in the Industry 4.0 environment are carried out by using a special toolbox. The advantages and disadvantages of the two planning methods are compared, and the joint space trajectory planning method is selected to study the planning of its third and fifth polynomials. The kinetic characteristics of the robot were simulated and tested by experimental methods, and the reliability of the simulation results of the kinetic characteristics was verified. The kinematic solutions of industrial robots and the results of multisolution optimization are simulated. The methods, theories, and strategies studied in this paper are slightly modified to provide theoretical and practical support for another dynamic simulation modeling of industrial robot kinematics with various geometries.

Quasi-optimal trajectory planning and control of a CRS A251 industrial robot

2002 ◽  
Vol 216 (4) ◽  
pp. 343-356
Author(s):  
J V Miro ◽  
A S White
Keyword(s):  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Industrial Robot ◽  
Minimum Principle ◽  
Terminal Phase ◽  
Planning Problem ◽  
Fundamental Parameter ◽  
Feedback Form ◽  
Open Chain ◽  
Optimal Trajectory Planning

A near-optimal solution to the path-unconstrained time-optimal trajectory planning problem is described in this paper. While traditional trajectory planning strategies are entirely based on kinematic considerations, manipulator dynamics are usually neglected altogether. The strategy presented in this work has two distinguishing features. Firstly, the trajectory planning problem is reformulated as an optimal control problem, which is in turn solved using Pontryagin's maximum/minimum principle. This approach merges the traditional division of trajectory planning followed by trajectory tracking into one process. Secondly, the feedback form compensates for the dynamic approximation errors derived from linearization and the fundamental parameter uncertainty of the dynamic equations of motion. This approach can cope with flexible robots as well as rigid links. The terminal phase of the motion is controlled by a feedforward controller to reduce chatter vibrations. Results from simulations and an on-line implementation to a general-purpose open-chain industrial manipulator, the CRS A251, confirm the validity of the approach and show that maximizing the capabilities of the device can lead to an overall improvement in the manipulator time response of up to 24 per cent, while retaining an acceptable overshoot and steady state error regime.

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.

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