Master the neural nervous system of robots. Dive deep into nodes, topics, and services to orchestrate complex humanoid behaviors.
ROS2 Core Concepts
Understand the foundational elements of ROS2, including its distributed architecture, nodes, topics, and services for inter-process communication.
Robotics Middleware
Explore the role of middleware in robotics, enabling seamless integration of hardware and software components for complex robotic systems.
Behavior Orchestration
Learn how to orchestrate complex humanoid behaviors using ROS2, from basic movements to advanced task execution.
Learning Outcomes:
ROS2 Basics
Fundamentals of ROS2 framework.
Nodes & Topics
Inter-process communication mechanisms.
Services & Actions
Request-response and long-running task patterns.
Advanced ROS2
Dive deeper into custom interfaces and advanced tools.
Bridge the sim-to-real gap. Leverage Gazebo and Unity to create high-fidelity virtual labs for safe and scalable AI training.
Sim-to-Real Gap
Bridge the gap between virtual simulations and real-world robot performance, ensuring robust and reliable operation.
Virtual Labs (Gazebo/Unity)
Leverage high-fidelity simulation environments like Gazebo and Unity to create safe and scalable virtual labs for AI training.
Physics-Based Simulation
Understand the principles of physics-based simulation for accurate modeling of robotic dynamics and interactions.
Learning Outcomes:
Simulation Setup
Setting up your first simulation environment.
Gazebo & Unity
Comparing and utilizing different simulation platforms.
Sim-to-Real Transfer
Techniques for transferring learned policies to real robots.
Advanced Simulation
Complex environments and multi-robot simulations.
Deploy intelligence to the edge. Explore hardware requirements, quantum-crypto trends, and real-time inference on NVIDIA Jetson platforms.
Edge AI Deployment
Deploy intelligence directly to the edge, optimizing AI models for real-time inference on robotic hardware.
Hardware Requirements
Explore the hardware requirements for AI-powered robots, including embedded systems and specialized processing units.
NVIDIA Isaac Platform
Utilize the NVIDIA Isaac platform for accelerated AI development, simulation, and deployment in robotics.
Learning Outcomes:
Isaac Platform Overview
Introduction to NVIDIA Isaac SDK and Sim.
Reinforcement Learning
Applying RL techniques in robotic control.
Model Deployment
Deploying trained models to edge devices.
Isaac ROS Integration
Combining Isaac with ROS for advanced robotics.
Explore the frontier of embodied AI. Understand Visual-Language-Action (VLA) models and the cognitive architectures driving next-generation humanoid robots.
Visual-Language-Action (VLA)
Understand how VLA models integrate vision, language, and action to enable more intelligent and versatile robotic behaviors.
Cognitive Architectures
Explore advanced cognitive architectures that drive next-generation humanoid robots, enabling reasoning and decision-making.
Embodied AI
Delve into the frontier of embodied AI, where AI systems learn and interact with the physical world through a robotic body.
Learning Outcomes:
VLA Fundamentals
Core concepts of Visual-Language-Action models.
Cognitive Architectures
Building intelligent decision-making systems.
Ethical AI in Robotics
Considering the ethical implications of advanced robotics.
Human-Robot Interaction
Designing intuitive and safe interactions with humanoids.
ROS2 & Robotics Middleware
Master the neural nervous system of robots. Dive deep into nodes, topics, and services to orchestrate complex humanoid behaviors.
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Digital Twin & Physics Sim
Bridge the sim-to-real gap. Leverage Gazebo and Unity to create high-fidelity virtual labs for safe and scalable AI training.
Learn More
Hardware & Edge AI
Deploy intelligence to the edge. Explore hardware requirements, quantum-crypto trends, and real-time inference on NVIDIA Jetson platforms.
Learn More