Capstone Project: Autonomous Humanoid for Voice-Commanded Tasks
Welcome to the Capstone Project! This is the culmination of your journey through the Physical AI & Humanoid Robotics Course. In this phase, you will apply all the knowledge and skills gained from Modules 1, 2, 3, and 4 to build a fully autonomous humanoid robot capable of understanding voice commands and executing complex tasks in a simulated environment.
1. Project Goal
The primary goal of the Capstone Project is to design, implement, and demonstrate an autonomous humanoid robot that can:
- Receive high-level voice commands from a human operator.
- Interpret these commands using natural language understanding.
- Plan and navigate through a simulated environment.
- Identify and locate specific objects.
- Perform manipulation tasks (e.g., picking and placing objects).
The project narrative is: "Autonomous Humanoid receiving voice → planning → navigation → object identification → manipulation"
2. Core Pipelines (Integration of Modules)
The Capstone Project requires the seamless integration of several key pipelines, each building upon the concepts learned in previous modules:
a) Voice Input Pipeline (Whisper -> LLM -> ROS 2 Actions)
This pipeline handles the human-robot interface, converting spoken commands into structured robotic instructions.
- Voice-to-Text: Utilize a Speech-to-Text (STT) system (e.g., OpenAI Whisper, as explored in Module 4) to transcribe spoken language into text.
- Language Understanding: Employ a Large Language Model (LLM, as explored in Module 4) to interpret the text, extract intent, and identify relevant entities (objects, locations).
- ROS 2 Action Generation: Translate the LLM's output into a sequence of discrete ROS 2 actions or service calls that the robot can execute.
b) Cognitive Planning Pipeline
This pipeline is responsible for breaking down high-level commands into a series of actionable sub-tasks and ensuring their logical execution.
- Task Decomposition: Transform an abstract command (e.g., "get me the cup") into a sequence of more specific actions (e.g., "navigate to table," "find cup," "grasp cup," "return cup").
- State Management: Keep track of the robot's current state, the environment's state, and the progress of the overall task.
- Decision Making: Make decisions at various points in the plan, such as re-planning if an obstacle is encountered or if an object is not found.
c) Navigation Pipeline (Isaac Sim + Nav2)
This pipeline enables the humanoid to move autonomously and safely within the simulated environment.
- Localization & Mapping: Use techniques like Visual SLAM (Simultaneous Localization and Mapping), potentially from Isaac Sim's capabilities or external ROS 2 packages, to build a map of the environment and determine the robot's position within it.
- Path Planning: Generate global and local paths to reach target locations while avoiding obstacles. ROS 2 Nav2 stack is a prime candidate for this.
- Motion Control: Execute the planned paths by generating appropriate velocity commands for the robot's base.
- Simulation Environment: All navigation will occur within Isaac Sim, leveraging its physics and rendering capabilities.
d) Object Identification and Manipulation Pipeline (URDF -> Controllers)
This pipeline focuses on the robot's ability to interact with objects in its environment.
- Object Perception: Utilize vision systems (e.g., from Isaac ROS or other sources, as explored in Module 3 and 4) to detect, identify, and estimate the 3D pose of target objects.
- Reachability Analysis: Determine if the robot's arm can reach the target object from its current position.
- Grasping Strategy: Plan a stable grasp for the object, considering its geometry and the robot's gripper capabilities.
- Manipulation Execution: Use the robot's URDF model and joint controllers to execute the planned reach and grasp actions.
3. Capstone Project Requirements
- The robot MUST respond to at least three distinct high-level voice commands (e.g., "Pick and Place", "Explore Room", "Follow Me").
- The robot MUST be able to navigate a predefined simulated environment in Isaac Sim to reach target locations.
- The robot MUST accurately identify and localize at least two distinct objects.
- The robot MUST successfully perform pick-and-place manipulation for at least one object.
- All components MUST be integrated using ROS 2 communication mechanisms.
- The entire system MUST run robustly in Isaac Sim.
4. Deliverables
- A fully integrated ROS 2 system running in Isaac Sim.
- Demonstration of the humanoid executing voice-commanded tasks.
- Codebase for all pipelines.
- Detailed
docs/capstone/overview.mdxanddocs/capstone/evaluation.mdx.
Conclusion
The Capstone Project brings together all the complex facets of Physical AI and Humanoid Robotics. Successfully completing this project will demonstrate a comprehensive understanding of ROS 2, advanced simulation, AI perception, natural language processing, and robot control. Good luck!