Get in Touch
 Duration 21 hours

Course Outline

Fundamentals of Computer Vision in Robotics

  • Exploring the scope of computer vision applications in the robotics domain
  • Addressing key challenges in visual perception and understanding
  • Configuring the development environment with OpenCV and Python

Essentials of Image Processing

  • Understanding image representation and manipulation techniques
  • Applying filtering, edge detection, and feature extraction methods
  • Working with color spaces and advanced segmentation techniques

Object Detection and Tracking via OpenCV

  • Implementing object detection using classical approaches (e.g., Haar cascades, HOG)
  • Tracking dynamic objects within video streams
  • Incorporating visual feedback loops into robotic system controls

Deep Learning for Enhanced Visual Perception

  • Introducing convolutional neural networks (CNNs) and their architecture
  • Training and deploying robust object detection models
  • Utilizing pre-trained architectures such as YOLO, SSD, and Faster R-CNN

Sensor Fusion and Depth Awareness

  • Fusing camera data with LiDAR and ultrasonic sensor inputs
  • Performing depth estimation and 3D spatial reconstruction
  • Enabling perception capabilities for obstacle avoidance and precise navigation

Vision-Driven Control and Decision Making

  • Applying computer vision techniques to robotic manipulation tasks
  • Implementing visual servoing and closed-loop control strategies
  • Achieving autonomous decision-making driven by visual inputs

Deployment and Optimization of Vision Models

  • Deploying models efficiently on embedded systems and edge devices
  • Optimizing inference speed for real-time application requirements
  • Troubleshooting issues and refining model accuracy

Conclusions and Future Directions

Requirements

  • A foundational understanding of core robotics concepts
  • Proficiency in Python programming
  • Basic familiarity with machine learning principles

Target Audience

  • Robotics Engineers
  • Computer Vision Practitioners
  • Machine Learning Engineers

Number of participants


Price per participant

Testimonials (2)

Upcoming Courses

Related Categories