A new generation of AI-powered robots continues to expand in use for manufacturing facilities, power plants, warehouses, and other industrial sites. Built on years of breakthroughs in deep learning and reinforcement learning, AI-powered robots have learned to handle various objects with minimum help from humans. MATLAB and Simulink are utilized as an intuitive learning environment for deep learning and control algorithms with a 3D virtual simulation environment to develop a new generation of AI-powered robots.

In this webinar, we will talk about robot modeling and simulation, ROS Connectivity and deployment, and to bring theory to practice, we will show you how to develop an AI-based autonomous mobile robot.

• Autonomous System Applications
• Developing Autonomous Ground Robots
• Autonomous Ground Robot Algorithms
• LIDAR-Based SLAM
• SLAM Map Builder App
• 3D SLAM and Egocentric Mapping
• Autonomous Robotics Applications:
  • Robotic Manipulators
  • Unmanned Aerial Vehicles (UAVs)
• Demo: Line Following Robot with Deep Learning

• gain a clear understanding of how MATLAB and Simulink can help you in your autonomous robotics application development projects.

• increase the use of automation and improve efficiency through the latest product capabilities of object detection for warehouse mobile robots and pick-and-place robots.

• reduce your robotics development time through the automatic CUDA code generation from the model, eliminating topical errors, and the use of simulation.
• reduce your UAVs’ development time through terrain classification, semantic segmentation, and the use of simulation.