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Learning Outcomes

Upon successful completion of this course, students will be able to:

  1. Design and Implement ROS 2-based Robotic Systems: Understand the core concepts of ROS 2 (Nodes, Topics, Services, Actions) and apply them to design modular and distributed robot control architectures, particularly for complex humanoid systems. This includes selecting appropriate QoS settings for real-time communication and integrating Python agents via rclpy.
  2. Utilize Digital Twin Simulations for Robotics Development: Create and manage high-fidelity digital twins using both Gazebo and Unity environments. Students will be proficient in building virtual worlds, simulating robot dynamics and physics, and modeling various sensors (LiDAR, depth cameras, IMUs) to accelerate testing and development workflows.
  3. Leverage NVIDIA Isaac Ecosystem for Advanced AI Robotics: Apply NVIDIA Isaac Sim for photorealistic simulation and synthetic data generation, and utilize Isaac ROS for hardware-accelerated perception and navigation on NVIDIA GPUs. This includes understanding the benefits of GPU acceleration for real-time humanoid control and perception.
  4. Develop Humanoid-Specific Navigation and Path Planning: Adapt and configure the Nav2 stack for bipedal humanoid movement, including gait-aware trajectory generation, footstep planning strategies, and sensor fusion techniques (IMU + VSLAM + depth camera) for stable navigation in uneven terrain.
  5. Integrate Vision-Language-Action (VLA) Systems in Robotics: Design and implement VLA pipelines that converge Large Language Models (LLMs), visual perception, and robot control. This involves using speech interfaces (e.g., OpenAI Whisper) for natural language command recognition, LLM-based cognitive planning, and multi-modal perception for robust scene understanding and action execution.
  6. Construct an Autonomous Humanoid Robot Prototype: Independently design, implement, and demonstrate a simulated autonomous humanoid robot capable of receiving voice commands, performing LLM-based cognitive planning, navigating an environment, executing object detection, and manipulating objects to complete a complex task, culminating in a capstone project.