A Comparison Among the Denavit - Hartenberg, the Screw Theory, and the Iterative Methods to Solve Inverse Kinematics for Assistant Robot Arm

Becerra, Yeyson; Arbulú, Mario; Ventura, Sebastián; Martínez, Fernando

doi:10.1007/978-3-030-26369-0_42

Cited by 9 publications

(5 citation statements)

References 15 publications

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“…The D-H method sets the orthonormal coordinate systems in each joint of the robotic manipulator, in such way that axis z k (where k is a counter determining the joint) matches the axis of movement of the joint k . 27 Once all the coordinate systems are positioned, the parameters θ k , d k , a k and α k are determined and they are placed in the homogeneous transformation matrix for the joint 28 –30…”

Section: Methodsmentioning

confidence: 99%

Path planning optimization of six-degree-of-freedom robotic manipulators using evolutionary algorithms

Šegota

Anđelić

Lorencin

et al. 2020

International Journal of Advanced Robotic Systems

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Lowering joint torques of a robotic manipulator enables lowering the energy it uses as well as increase in the longevity of the robotic manipulator. This article proposes the use of evolutionary computation algorithms for optimizing the paths of the robotic manipulator with the goal of lowering the joint torques. The robotic manipulator used for optimization is modelled after a realistic six-degree-of-freedom robotic manipulator. Two cases are observed and these are a single robotic manipulator carrying a weight in a point-to-point trajectory and two robotic manipulators cooperating and moving the same weight along a calculated point-to-point trajectory. The article describes the process used for determining the kinematic properties using Denavit–Hartenberg method and the dynamic equations of the robotic manipulator using Lagrange–Euler and Newton–Euler algorithms. Then, the description of used artificial intelligence optimization algorithms is given – genetic algorithm using random and average recombination, simulated annealing using linear and geometric cooling strategy and differential evolution. The methods are compared and the results show that the genetic algorithm provides best results in regard to torque minimization, with differential evolution also providing comparatively good results and simulated annealing giving the comparatively weakest results while providing smoother torque curves.

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Section: Methodsmentioning

confidence: 99%

Path planning optimization of six-degree-of-freedom robotic manipulators using evolutionary algorithms

Šegota

Anđelić

Lorencin

et al. 2020

International Journal of Advanced Robotic Systems

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show abstract

“…The inverse problem [6], [9],[11] consists in evaluating the articular coordinates corresponding to a given position of the terminal organ, according to the Cartesian coordinates. The inverse geometrical model is used to calculate the position of each robot link as a function of the position and orientation of the end organ.…”

Section: 2inverse Modelmentioning

confidence: 99%

“…These operations make it possible to isolate and identify the articular variables we are looking for successively. In this case we proceed as follows: By multiplying (5) on both sides by we get (6). *…”

Section: 2inverse Modelmentioning

confidence: 99%

Modeling and control a Robot serving a CNC Didactic Milling Machine

ECH-CHHIBAT¹

2020

IJATCSE

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Robotics is a very dynamic field, which has been evolving diligently in these recent years. The pandemic disease hitting the world actually is accelerating significantly this development of robotics. The robot is a main factor that helps to ensure the distanciating in order to minimize the spread of this disease (Covid-19).Our contribution concerns mechanical production workshops, in this case, the automatic loading and unloading of a numerically controlled teaching machine, which implanted in our laboratory. The purpose is to reduce the manual manipulation of machine's parts and organs as much as possible, thus limiting the disease's spread by touch. In this work, we have developed all the models necessary to control the serial robot with six degrees of freedom. Three of those degrees control the position of the effector, and the three others orient the wrist. For this context, the direct and reversed geometric model, kinematic model and dynamic model were determined. A robot position and speed control methodology is proposed. Many simulations have been effectuated to properly validate the specific models sought

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“…This method converts the target coordinates into the angular motion of each robot joint. Various approaches such as Denavit-Hartenberg (D-H) [5], Screw Theory and Iterative Methods [6] are used to solve the inverse kinematics problem. In addition, instead of solving inverse kinematics equations, statistical approaches called soft computation methods in the literature can be used [7,8].…”

Section: Introductionmentioning

confidence: 99%

RRR Robotik Kol için Çok Katmanlı Algılayıcı ve Ters Kinematik Karşılaştırması

et al. 2024

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In this study, the position control simulation of a 3 Degree of Freedom (3DOF) robot arm was compared with machine learning and inverse kinematic analysis separately. The considered robot arm is designed in RRR pattern. In the inverse kinematic analysis of the robot arm, the geometric approach and the analytical approach are used together. Multi-Layer Perceptron (MLP) was used as a machine learning method. Some of the coordinate data that the robot arm can reach in the working space are selected and the MLP model is trained with these data. When training was done with MLP machine learning method, the correlation coefficient (R2) was obtained as 1. Coordinates of 3 different geometric models (helix, star and daisy) that can be included in the working space are used as test data of the MLP model. These tests are simulated in 3D in MATLAB environment. The simulation results were compared with the inverse kinematics analysis data. As a result, Mean Relative Error (MRE) values for helix, star and daisy shapes were calculated as 0.0007, 0.0033 and 0.0011, respectively, in the tests performed. Mean Squared Error (MSE) values were obtained as 0.0034, 0.0065 and 0.0040, respectively. This confirms that the proposed MLP model can operate this system at the desired stability.

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A Comparison Among the Denavit - Hartenberg, the Screw Theory, and the Iterative Methods to Solve Inverse Kinematics for Assistant Robot Arm

Cited by 9 publications

References 15 publications

Path planning optimization of six-degree-of-freedom robotic manipulators using evolutionary algorithms

Path planning optimization of six-degree-of-freedom robotic manipulators using evolutionary algorithms

Modeling and control a Robot serving a CNC Didactic Milling Machine

RRR Robotik Kol için Çok Katmanlı Algılayıcı ve Ters Kinematik Karşılaştırması

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