Vision AI for Robotics using ROS 2 (Cohort 3)
Overview
Build AI-Powered Robot Perception using Vision Language Models (VLMs)
Vision Language Models (VLMs) are revolutionizing robot perception by enabling robots to understand and reason about their surroundings using both visual and natural language inputs. In this hands-on workshop, participants will learn how to integrate lightweight VLMs with ROS 2 to develop intelligent robot perception applications that run efficiently on standard laptops, with or without an NVIDIA GPU. The workshop will also explore GPU acceleration using NVIDIA CUDA to optimize inference performance for real-time robotic applications.
Meet Your Instructor
Lentin Joseph — Author of 11 ROS & Robotics books, Co-Founder of RUNTIME Robotics, and TEDx Speaker.
By the End You'll Walk Away With
A complete ROS 2 AI Vision application in a robot
Hands-on experience with Vision Language Models (VLMs)
ROS 2 image processing pipeline using OpenCV
Image Captioning and Visual Question Answering (VQA)
ROS 2 Services for Vision AI inference
Knowledge of CPU deployment and NVIDIA GPU acceleration
Who Should Attend
ROS 2 Developers
Robotics Engineers
AI & Computer Vision Engineers
Students and Researchers
Anyone interested in intelligent robot perception
What You'll Learn
Introduction to Vision Language Models
ROS 2 camera and image pipeline
Running lightweight VLMs on CPU
Image Captioning
Visual Question Answering
ROS 2 Topics, Services and Parameters
Performance optimization
Optional NVIDIA GPU acceleration
What You'll Need
Laptop (Ubuntu 24.04 recommended)
Python 3.10+
ROS 2 Jazzy
USB Webcam
Minimum 8 GB RAM (16 GB recommended)
Internet connection
Why Now?
Vision Language Models are becoming a key technology for next-generation robotics and Physical AI. Learning how to integrate them with ROS 2 gives developers practical skills for building intelligent robot perception systems used in research and industry.
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