A method for the automatic generation of inverse kinematic maps in modular robotic systems

Mayyas, Mohammad; Mellish, Rochelle

doi:10.1177/1729881416662790

Cited by 3 publications

(2 citation statements)

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“…Mayyas and Mellish [5] presented a computationally efficient joint space approach for determining a modular robotic system's configuration for a given route. Akkar and Amir [6] derived and developed an analytical solution for the Kinematics of a 6 DOF Robot Arm from DFROBOT that gives correct joint angles using a newly developed system solver.…”

Section: Introductionmentioning

confidence: 99%

Surgical Self- steering Robot using Artificial Neural Network

Mahfouz,

Gamal,

Awad

et al. 2023

Preprint

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The aim of this work is to design a robot that can be used in surgery and can remove tumors by accurately and safely following contours. This is achieved by the medical imaging set such as DICOM-formatted images from several sources (CT, MRI, and Ultrasound) of these tumors using artificial neural networks. The workspace of a suggested 7 degrees of freedom robot is defined by calculating the position of the end effector for multiple positions of its links using DH tables and feed-forward kinematics. The data obtained are used to train three artificial neural networks to get the inverse kinematics. The suggested neural networks are the Generalized Regression Neural Network, Radial Basis, and Feed Forward. A training course for inverse kinematics of 23328 workspace points of the end effector of the suggested robot is used for training the three neural networks. The most accurately trained one was found to be the Feed-Forward neural network. It shows a root mean square error for those points of 2.08 mm and a training time of 1236 seconds and is to be applied to steer the robot links. The patient medical images are digitized using the image processing toolbox of MATLAB. The data obtained is to be fed to the superior neural network to get the robot links positions needed to move the end effector mounted with a cutter to follow the tumor contour accurately. The absolute error distance between the corresponding points of the contours resulting from testing the trained Feed-Forward NN with 51 points of a contour doesn’t exceed 2.08 mm.

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Section: Introductionmentioning

confidence: 99%

Surgical Self- steering Robot using Artificial Neural Network

Mahfouz,

Gamal,

Awad

et al. 2023

Preprint

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“…3,7 Moreover, because of these advantages, it can be widely applied in various research areas. 8 –11…”

Section: Introductionmentioning

confidence: 99%

A novel second subproblem for two arbitrary axes of robots

Wang

Zhang

et al. 2018

International Journal of Advanced Robotic Systems

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The Paden-kahan subproblem is a simple and flexible method to solve the closed-form inverse resolution but limited by the geometrical structure of robots, which is very difficult to be kept because of processing and installation. Therefore, a closed-form solution on arbitrary configurations is an important issue in the field of robotic inverse kinematics. A novel second subproblem is firstly proposed in this study based on the product-ofexponentials model adapting to the two arbitrary axes without geometric constraints (parallel, vertical, disjoint, and so on). Furthermore, the algebraic methods involving the basic properties of the screw theory and Rodrigues' rotation formula are employed for the solution, which makes the constraint equations of the second subproblem solvable for arbitrary configurations. This methodology can be applied to the inverse solutions of 5-degree-offreedom robots that satisfies the Pieper criterion and can express the inverse solutions via two common formulas. Finally, the simulation and the real-world experiment demonstrated the accuracy of the method and the validity, respectively.

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Analysis and Measurement of Human Motion: Modern Protocols and Clinical Considerations

Ancillao¹

2016

J Robot Mech Eng Resr

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The study of movement has always fascinated artists, photographers and researchers. Across the years, several attempts to capture, freeze, study and reproduce motion were made. Nowadays, the possibility to have quantitative data may support the diagnosis and treatment of many pathologies. Thus, in many rehabilitation facilities, a motion analysis laboratory is considered a must-have for diagnosis and patient's monitoring. This paper reviews the first historical attempts, based on photography, and their earliest results, till the state-of-the-art technology used today, i.e. the optoelectronic system.Working principle of the optoelectronic system is described as well as its application and setup in the clinical practice. Modern functional evaluation protocols are reviewed, with pro and cons and examples of clinical results and discoveries. Results of measurements conducted on subjects with neuro-motor pathologies are reviewed. Special attention is paid to the most common motion analysis exam that is nowadays worldwide standardized, i.e. the Gait Analysis. Examples of Gait Analysis on subjects with pathology and follow-up are reviewed.

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A method for the automatic generation of inverse kinematic maps in modular robotic systems

Cited by 3 publications

References 32 publications

Surgical Self- steering Robot using Artificial Neural Network

Surgical Self- steering Robot using Artificial Neural Network

A novel second subproblem for two arbitrary axes of robots

Analysis and Measurement of Human Motion: Modern Protocols and Clinical Considerations

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