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.

Trajectory Planning for Manufacturing Robots: Algorithm Definition and Experimental Results

2010 ◽  
Author(s):  
Alessandro Gasparetto ◽  
Albano Lanzutti ◽  
Renato Vidoni ◽  
Vanni Zanotto
Keyword(s):  
Trajectory Planning ◽  
Execution Time ◽  
Robot Manipulator ◽  
Experimental Tests ◽  
Minimum Time ◽  
Experimental Results ◽  
Kinematic Constraints ◽  
Planning Algorithm ◽  
Automatic Choice

In this paper an analysis of the experimental results yielded by 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 trajectory, and the kinematic constraints of the robot manipulator under test. The need for a fast execution and the need for a smooth trajectory are taken into account by adjusting the values of two weights, whose suitable values are set with an “automatic” choice algorithm. The outcomes of the tests are compared with both simulations and experimental results obtained by using a “classic” spline trajectory planning algorithm. The experimental tests are carried out by using an accelerometer mounted on a Cartesian robot.

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.

Trajectory planning for coordinately operating robots

1990 ◽  
Vol 4 (3) ◽  
pp. 165-177 ◽  
Author(s):  
Y. P. Chien ◽  
Qing Xue
Keyword(s):  
Trajectory Planning ◽  
Three Dimensional ◽  
Initial Position ◽  
Minimum Time ◽  
Future Research ◽  
Rigid Object ◽  
Redundant Robots ◽  
Planning Algorithm ◽  
The Common ◽  
Joint Velocity

An efficient locally minimum-time trajectory planning algorithm for coordinately operating multiple robots is introduced. The task of the robots is to carry a common rigid object from an initial position to a final position along a given path in three-dimensional workspace in minimum time. The number of robots in the system is arbitrary. In the proposed algorithm, the desired motion of the common object carried by the robots is used as the key to planning of the trajectories of all the non-redundant robots involved. The search method is used in the trajectory planning. The planned robot trajectories satisfy the joint velocity, acceleration and torque constraints as well as the path constraints. The other constraints such as collision-free constraints, can be easily incorporated into the trajectory planning in future research.

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 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.

scholarly journals Modeling and Identification of an Industrial Robot with a Selective Modal Approach

2020 ◽  
Vol 10 (13) ◽  
pp. 4619 ◽  
Author(s):  
Matteo Bottin ◽  
Silvio Cocuzza ◽  
Nicola Comand ◽  
Alberto Doria
Keyword(s):  
Dynamic Model ◽  
Material Removal ◽  
Industrial Robot ◽  
Joint Stiffness ◽  
Industrial Applications ◽  
Industrial Robots ◽  
Robotic Assembly ◽  
Machined Surface ◽  
Modal Approach ◽  
Removal Processes

The stiffness properties of industrial robots are very important for many industrial applications, such as automatic robotic assembly and material removal processes (e.g., machining and deburring). On the one hand, in robotic assembly, joint compliance can be useful for compensating dimensional errors in the parts to be assembled; on the other hand, in material removal processes, a high Cartesian stiffness of the end-effector is required. Moreover, low frequency chatter vibrations can be induced when low-stiffness robots are used, with an impairment in the quality of the machined surface. In this paper, a compliant joint dynamic model of an industrial robot has been developed, in which joint stiffness has been experimentally identified using a modal approach. First, a novel method to select the test configurations has been developed, so that in each configuration the mode of vibration that chiefly involves only one joint is excited. Then, experimental tests are carried out in the selected configurations in order to identify joint stiffness. Finally, the developed dynamic model of the robot is used to predict the variation of the natural frequencies in the workspace.

A practical approach for minimum‐time trajectory planning for industrial robots

2010 ◽  
Vol 37 (1) ◽  
pp. 51-61 ◽  
Author(s):  
Joonyoung Kim ◽  
Sung‐Rak Kim ◽  
Soo‐Jong Kim ◽  
Dong‐Hyeok Kim
Keyword(s):  
Trajectory Planning ◽  
Industrial Robots ◽  
Minimum Time ◽  
Practical Approach
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