HMOD102 - Advanced Humanoid Robotics in Action
Integrating Generative AI ChatGPT into your Humanoid Robots!
HMOD102 - Advanced Humanoid Robotics in Action free download
Integrating Generative AI ChatGPT into your Humanoid Robots!
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 capabilities
o Role of ChatGPT in AI-human interaction
o Recent breakthroughs in humanoid robotics (Figure 2, Optimus, Unitree, Boston Dynamics)
o Introduction to Yanshee humanoid robot and its programming environment
o Setting up the environment for ChatGPT integration with Yanshee
· Tasks: Set up OpenAI GPT-4 API for interaction with humanoid robots
Module/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 ChatGPT
o APIs and frameworks for connecting robots to cloud-based AI models
o Programming humanoid robots to generate natural language responses
o Use cases: ChatGPT-powered robots in customer service, healthcare
o Building basic conversation flows between humans and humanoids
· Tasks: Implement a basic ChatGPT-powered conversational interface on Yanshee
Module/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 AI
o Emotion detection and personalized interaction with robots
o Handling ambiguous and incomplete inputs with AI
o Optimizing conversation flows for different use cases
o 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-making
o Training humanoids to understand complex scenarios and offer solutions
o Integrating external data sources (e.g., databases, APIs) for smarter responses
o Cognitive AI in humanoid robotics: Learning from interactions
o Designing humanoids capable of multi-tasking
· Tasks: Lab on integrating ChatGPT for task-oriented decision-making
Module/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 loops
o Teaching humanoid robots to learn from user interactions
o Adaptive behavior: Responding to changing environments
o Case study: Adaptive humanoids in education and therapy
o Evaluating performance and improving conversational accuracy over time
· Tasks: Develop an adaptive learning system for Yanshee using ChatGPT and real-time feedback
Module/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 AI
o Developing full-stack robotic applications with ChatGPT
o Use of cloud platforms for AI model hosting (AWS, Google Cloud)
o Advanced humanoid tasks: real-time navigation and manipulation
o Testing and refining robot performance in real-world settings
· Tasks: Develop a fully functioning humanoid system using ChatGPT for dynamic interactions
Module/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 feedback
Module/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 algorithms
o 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 AI
o Emotional response generation through ChatGPT
o Practical applications: Social robots for therapy, customer service, entertainment
o Ethical considerations of emotionally responsive robots
o Designing emotionally intelligent humanoid systems
· Tasks: Program Yanshee to detect and respond to emotional cues using ChatGPT
Module/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 robots
o ChatGPT as a mediator in human-robot collaboration
o Case study: AI-driven cobots in manufacturing and logistics
o Coordinating complex tasks between robots and humans
· Tasks: Create a collaborative task between Yanshee and another robot using ChatGPT
Module/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 avoidance
o Generative AI-driven task scheduling and execution
o Gait control algorithms for humanoid locomotion
o Using ChatGPT for dynamic task prioritization
o Case study: Humanoid robots in complex, changing environments
· Tasks: Implement advanced mobility control and AI-driven task execution on Yanshee
7 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. 2/2
12 Lecture PPTs can be downloadable from each section at Downloadable Resource for your reference.
