w Dynamically Modified Penalty Function for Control of Mitsubishi Robotic Arm in Real Time

Zwonarz, Wojciech; Turnau, Andrzej

doi:10.1016/j.ifacol.2018.11.420

Cited by 1 publication

(1 citation statement)

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“…e system consists of a highprecision 6-DoF self-balancing arm that is able to move in passive and active modes, allowing physicians to accurately insert needles [3]. Zwonarz and Turnau believed that trajectory optimization must be done for the optimization of industrial robots [4]. Smyrnaiou et al conducted a comparative study of classical control methods for testing mathematical models.…”

Section: Related Workmentioning

confidence: 99%

Design and Simulation Analysis of Trajectory Planning Algorithm for 6-DoF Manipulator Based on Deep Learning

Zhuang

Ding

2022

Mobile Information Systems

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At present, the robot developed only has partial intelligence, and it cannot be well controlled independently for some jobs, so it should optimize its path and trajectory. However, as an industrial robotic arm robot necessary for advanced industrial manufacturing enterprises, it has been replacing humans to perform simple and repetitive actions, and it is doing better and better. For the six-degree-of-freedom (6-DoF) manipulator, this paper aims to optimize the trajectory planning of the manipulator based on deep learning technology. Therefore, this paper presents a fuzzy control algorithm for the trajectory planning of the manipulator based on the neural network algorithm. The experimental results show that for the established three-joint dynamic model, the moment received by joint 1 is the largest, followed by joint 2, and joint 3 is the smallest, which can better simulate the trajectory of the robotic arm.

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Section: Related Workmentioning

confidence: 99%