HMOD102 - Advanced Humanoid Robotics in Action

所在平台: Udemy

课程主页: https://www.udemy.com/course/hmod102-advanced-humanoid-robotics-in-action/

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课程名称:HMOD102 - 先进类人机器人实战 课程概述:本课程为学生提供前沿技能,以运用生成式人工智能(尤其是ChatGPT)开发类人机器人,提升其在医疗、客户服务和工业自动化等领域的实际应用。学生将构建具备动态交互、情感检测和自主执行任务能力的AI驱动类人机器人。课程采用实践操作的方法,针对寻求基于项目学习和具备市场需求技能的Udemy学习者而设计。 在本课程中,学生将探讨将生成式AI与Yanshee类人机器人结合的革命性潜力,创造出更智能、反应更快且能够执行复杂任务的机器人,进而进行人类般的对话并自主适应动态环境。课程重点关注ChatGPT的创新应用,开辟机器人开发的新可能性,使学习者处于类人机器人革命的前沿。 课程结束时,学生将能够: - 将ChatGPT与类人机器人集成,增强沟通和决策能力。 - 编程机器人实现实时、人性化的人机交互。 - 设计具备复杂问题解决能力的自主AI类人机器人。 - 搭建AI驱动的类人机器人全栈系统,应用于特定行业(医疗、教育、娱乐)。 - 开发能通过生成式AI模型实时反馈适应行为的机器人。 每周模块大纲: - 第1周:生成式AI在机器人中的应用 - 第2周:与Yanshee集成ChatGPT - 第3周:使用ChatGPT增强人机交互 - 第4周:生成式AI在类人机器人自主决策中的应用 - 第5周:类人机器人中的自适应学习与反馈系统 - 第6周:全栈开发:构建智能类人机器人 - 第7周:期中项目展示 - 第8周:类人机器人的情感智能 - 第9周:与ChatGPT的协作机器人技术 - 第10周:基于AI的高级移动性与任务执行及总结 该课程包括实践任务、案例研究以及基于Python的实验演示,旨在帮助学生将理论知识转化为实际应用。通过完成这些任务,学生将能够编程控制类人机器人的移动,集成ChatGPT进行智能对话,并开发情感检测系统等。 本课程适合希望在AI和机器人领域获得技术技能并参与行业发展的学习者。

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This course equips students with cutting-edge skills to develop humanoid robots using Generative AI, specifically ChatGPT, to enhance real-world applications in industries such as healthcare, customer service, and industrial automation. Students will build AI-powered humanoids capable of dynamic interactions, emotion detection, and autonomous task execution. Designed with a practical, hands-on approach, this course appeals to Udemy learners seeking project-based learning and in-demand skills for careers in AI and robotics.This advanced course takes humanoid robotics to the next frontier by integrating Generative AI, specifically OpenAI's ChatGPT, with Yanshee humanoid robots. Students will explore the revolutionary potential of Generative AI in creating more intelligent, responsive, and interactive humanoids capable of performing complex tasks, holding human-like conversations, and autonomously adapting to dynamic environments. The course focuses on innovative applications of ChatGPT, opening new possibilities in robotics development, and positioning learners at the cutting edge of the humanoid robotics revolution.By the end of this course, students will be able to:Integrate ChatGPT and other Generative AI models with humanoid robots to enhance communication and decision-making capabilities.Program humanoid robots for real-time, natural human-robot interaction using Generative AI.Design autonomous, AI-powered humanoids capable of complex problem-solving.Build full-stack humanoid systems with AI-driven capabilities for specific industries (healthcare, education, entertainment).Develop humanoids capable of adapting their behaviors using real-time feedback from Generative AI models.Course Syllabus can be found and downloadable at Section #1: Downloadable Resource Weekly Module Schedule: Module/Week 1: Introduction to Generative AI in Robotics· This Module Learning Objectives:By the end of this course, students will be able to:o Understand the role of Generative AI in humanoid robotics.o Explore ChatGPT's potential to improve communication and interaction between robots and humans.o Set up and integrate ChatGPT with Yanshee humanoid robots.o Examine recent breakthroughs in humanoid robots from companies like Boston Dynamics and Unitree.· Topics:o Overview of Generative AI and its capabilitieso Role of ChatGPT in AI-human interactiono Recent breakthroughs in humanoid robotics (Figure 2, Optimus, Unitree, Boston Dynamics)o Introduction to Yanshee humanoid robot and its programming environmento Setting up the environment for ChatGPT integration with Yanshee· Tasks: Set up OpenAI GPT-4 API for interaction with humanoid robotsModule/Week 2: ChatGPT Integration with Yanshee· This Module Learning Objectives:By the end of this course, students will be able to:o Integrate GPT-4 into Yanshee's communication systems.o Program humanoid robots to use Generative AI for dynamic conversational interactions.o Implement APIs for real-time cloud-based AI communication.o Develop use cases for ChatGPT-powered robots in industries such as healthcare and customer service.· Topics:o Connecting Yanshee's communication system to ChatGPTo APIs and frameworks for connecting robots to cloud-based AI modelso Programming humanoid robots to generate natural language responseso Use cases: ChatGPT-powered robots in customer service, healthcareo Building basic conversation flows between humans and humanoids· Tasks: Implement a basic ChatGPT-powered conversational interface on YansheeModule/Week 3: Enhancing Human-Robot Interaction Using ChatGPT· This Module Learning Objectives:By the end of this course, students will be able to:o Design conversational flows for humanoid robots using Generative AI.o Implement emotion detection and personalized interaction capabilities in humanoid robots.o Create intelligent responses based on ambiguous and incomplete inputs.o Address ethical considerations for AI-human interactions (e.g., disclosing robot identity).· Topics:o Designing natural conversations with Generative AIo Emotion detection and personalized interaction with robotso Handling ambiguous and incomplete inputs with AIo Optimizing conversation flows for different use caseso Ethical considerations: When should humanoid robots disclose they are AI?Tasks: Create an intelligent conversational agent on Yanshee for specific user scenarios (e.g., healthcare assistant)Module/Week 4: Generative AI for Autonomous Decision-Making in Humanoids· This Module Learning Objectives:By the end of this course, students will be able to:o Design conversational flows for humanoid robots using Generative AI.o Implement emotion detection and personalized interaction capabilities in humanoid robots.o Create intelligent responses based on ambiguous and incomplete inputs.o Address ethical considerations for AI-human interactions (e.g., disclosing robot identity).· Topics:o Using ChatGPT for real-time problem-solving and decision-makingo Training humanoids to understand complex scenarios and offer solutionso Integrating external data sources (e.g., databases, APIs) for smarter responseso Cognitive AI in humanoid robotics: Learning from interactionso Designing humanoids capable of multi-tasking· Tasks: Lab on integrating ChatGPT for task-oriented decision-makingModule/Week 5: Adaptive Learning and Feedback Systems in Humanoids· This Module Learning Objectives:By the end of this course, students will be able to:o Implement adaptive learning using reinforcement learning and generative feedback loops.o Teach humanoid robots to learn from real-time human interactions.o Develop systems that allow robots to adapt to changing environments.o Analyze case studies of adaptive robots in fields like education and therapy.· Topics:o Reinforcement learning vs. generative feedback loopso Teaching humanoid robots to learn from user interactionso Adaptive behavior: Responding to changing environmentso Case study: Adaptive humanoids in education and therapyo Evaluating performance and improving conversational accuracy over time· Tasks: Develop an adaptive learning system for Yanshee using ChatGPT and real-time feedbackModule/Week 6: Full-Stack Development: Building Intelligent Humanoids· This Module Learning Objectives:By the end of this course, students will be able to:o Integrate AI with hardware components (sensors, motors, cameras) for humanoid robots.o Build full-stack applications that utilize ChatGPT for humanoid interactions.o Use cloud platforms for AI model deployment and processing.o Test and refine humanoid robot performance in real-world scenarios.· Topics:o Hardware integration: Sensors, motors, and cameras with AIo Developing full-stack robotic applications with ChatGPTo Use of cloud platforms for AI model hosting (AWS, Google Cloud)o Advanced humanoid tasks: real-time navigation and manipulationo Testing and refining robot performance in real-world settings· Tasks: Develop a fully functioning humanoid system using ChatGPT for dynamic interactionsModule/Week 7: Midterm Project Presentation· This Module Learning Objectives:By the end of this course, students will be able to:o Present a functional humanoid robot integrated with ChatGPT.o Demonstrate the robot's conversational and interactive capabilities.o Evaluate peer feedback and refine robot designs.o Apply learned skills to improve robot functionality and task performance.· Tasks: Midterm project presentations; peer and instructor feedbackModule/Week 8: Emotional Intelligence in Humanoids· This Module Learning Objectives:By the end of this course, students will be able to:o Equip humanoid robots with emotion detection algorithmso Create AI-driven emotional responses in robots for social interactions.o Explore applications of emotionally intelligent robots in healthcare and customer service.o Evaluate ethical considerations when designing emotionally responsive robots.· Topics:o Emotion detection algorithms for Generative AIo Emotional response generation through ChatGPTo Practical applications: Social robots for therapy, customer service, entertainmento Ethical considerations of emotionally responsive robotso Designing emotionally intelligent humanoid systems· Tasks: Program Yanshee to detect and respond to emotional cues using ChatGPTModule/Week 9: Collaborative Robotics (Cobot) with ChatGPT· This Module Learning Objectives:By the end of this course, students will be able to:o Design collaborative humanoids using ChatGPT as a communication mediator.o Develop multi-agent systems for robots to collaborate with humans and other robots.o Program robots to coordinate tasks in real-time for manufacturing and logistics.o Analyze case studies on AI-powered cobots in industry.· Topics:o Generative AI in multi-agent systems (robot teams)o Designing collaboration protocols for humanoid robotso ChatGPT as a mediator in human-robot collaborationo Case study: AI-driven cobots in manufacturing and logisticso Coordinating complex tasks between robots and humans· Tasks: Create a collaborative task between Yanshee and another robot using ChatGPTModule/Week 10: Advanced Mobility and Task Execution Using AI & Capstone & Granulations!· This Module Learning Objectives:By the end of this course, students will be able to:o Implement advanced mobility features using AI-driven control algorithms.o Enable humanoids to perform complex task scheduling and execution.o Develop motion planning for humanoid robots to navigate dynamic environments.o Explore real-world case studies on robots operating in challenging settings.· Topics:o Advanced motion planning and obstacle avoidanceo Generative AI-driven task scheduling and executiono Gait control algorithms for humanoid locomotiono Using ChatGPT for dynamic task prioritizationo Case study: Humanoid robots in complex, changing environments· Tasks: Implement advanced mobility control and AI-driven task execution on Yanshee7 Lab Demos using Python on Yanshee Humanoid Platform (*Python source code * is available @Udemy Section/Class!): 1. Control Yanshee Humanoid Movement: forward, left turn, right turn, backward, dance, etc.;2. Integrate ChatGPT APIs to enable Humanoid to have intelligent conversation (ChatBot) 1/2;3. Integrate ChatGPT APIs to enable Humanoid to have intelligent conversation (ChatBot) 2/2;4. Detect the human facial Emotion such as Smile, Sad, Happy, Bored, etc 1/2;5. Detect the human facial Emotion such as Smile, Sad, Happy, Bored, etc 2/2;6. Recognize the human Gestures like wave hand, welcome, bye-bye, etc. 1/2;7. Recognize the human Gestures like wave hand, welcome, bye-bye, etc. 2/212 Lecture PPTs can be downloadable from each section at Downloadable Resource for your reference.

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