使用强化学习的 2DoF 机械臂

Q2 Engineering
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引用次数: 0

摘要

2DoF机械臂强化学习旨在开发一种智能系统,该系统可以使用强化学习技术学习控制具有两个自由度的机械臂。这里的概念包括使用一个模拟环境,在这个环境中,机械臂可以与不同的物体相互作用,并学习执行诸如到达、抓取和移动物体等任务。这个想法旨在提高工业和制造业应用中机械臂控制的效率和有效性,使它们能够以良好的精度和速度执行复杂的任务。概述了所提出的系统的目标、方法和结果,展示了该技术在控制机械臂及其在自动化中的应用的潜力
本文章由计算机程序翻译,如有差异,请以英文原文为准。
2DoF Robotic Arm using Reinforcement Learning
The 2DoF Robo-Arm Reinforcement Learning aims to develop an intelligent system that can learn to control a robotic arm with two degrees of freedom using reinforcement learning techniques. The concept here involves the use of a simulated environment in which the robotic arm can interact with different objects and learn to perform tasks such as reaching, grasping, and moving objects. The idea here seeks to improve the efficiency and effectiveness of robotic arm control in industrial and manufacturing applications, enabling them to perform complex tasks with good accuracy and speed. The overview of the proposed system’s objectives, methodology, and results, demonstrating the potential of this technology to control Robotic Arm and also its use in Automation are discussed here
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