Course Code: physicalairoboauto
Duration: 21 hours
Prerequisites:
  • 机器人和自动化系统的基础知识
  • 精通程式设计,最好 Python
  • 熟悉 AI 基础知识

观众

  • Robotics 工程师
  • 自动化专家
  • AI 开发人员
Overview:

Physical AI 将人工智慧和机器人技术相结合,创造出能够自主决策并与物理环境交互的机器。

这种讲师指导的现场培训(在线或现场)面向希望提高设计、程式设计和部署智慧机器人系统以实现自动化等技能的中级参与者。

在本次培训结束时,参与者将能够:

  • 了解 Physical AI 的原理及其在机器人和自动化中的应用。
  • 为动态环境设计和程式设计智慧机器人系统。
  • 实施 AI 模型,以便在机器人中进行自主决策。
  • 利用模拟工具进行机器人测试和优化。
  • 解决感测器融合、实时处理和能源效率等挑战。

课程形式

  • 互动讲座和讨论。
  • 大量的练习和练习。
  • 在即时实验室环境中动手实施。

课程自定义选项

  • 要申请本课程的定制培训,请联系我们进行安排。
Course Outline:

Physical AI 和 Robotics 简介

  • Physical AI及其演变概述
  • 工业自动化及其他领域的应用
  • 智慧机器人系统的关键部件

Robotics 系统设计

  • 机器人的机械设计原则
  • 感测器和执行器的集成
  • 电力系统和能源效率

适用于 Robotics 的 AI 模型

  • 使用机器学习进行感知和决策
  • 机器人中的强化学习
  • 为机器人系统构建 AI 管道

实时感测器集成

  • 感测器融合技术
  • 处理来自 LiDAR、相机和其他感测器的数据
  • 即时导航和避障

类比和测试

  • 使用 Gazebo 和 MATLAB Robotics Toolbox 等模拟工具
  • 动态环境建模
  • 性能评估和优化

自动化和部署

  • Programming 用于工业自动化的机器人
  • 为重复性任务开发工作流程
  • 确保部署的安全性和可靠性

高级主题和未来趋势

  • 协作机器人 (cobots) 和人机交互
  • 机器人技术的伦理和监管考虑因素
  • Physical AI 自动化的未来

总结和后续步骤

Sites Published:

United Arab Emirates - Physical AI for Robotics and Automation

Qatar - Physical AI for Robotics and Automation

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