Join us to learn how to apply AI for robotics development, including human-robot interaction with ChatGPT and autonomy algorithms for perception, motion planning, and control. Discover how AI applications in robotics have expanded to object identification, pose estimation, and motion planning.
Learn about AI-enabled robotics applications in various industries, such as manufacturing facilities, power plants, and warehouses. Warehouse bin-picking using deep learning and reinforcement learning to enable robots to handle various objects with minimal human assistance, reducing workplace injuries due to repetitive motions.
Examples from the livestream:
• Bin picking robot: [ Ссылка ]
• Deep Learning-Based Sampler for Motion Planning: [ Ссылка ]
• Accelerate Motion Planning with Deep-Learning-Based Sampler: [ Ссылка ]
• Train SAC Agent for Ball Balance Control: [ Ссылка ]
With MATLAB and Simulink, you can design, test, and deploy your AI applications for intelligent collaborative robots (Cobots), Autonomous Mobile Robots (AMR), UAVs, or other robotics systems. Reduce development time and time to market by taking advantage of Model-Based Design tools for implementing AI in robotics and autonomous systems.
You will gain insights on:
• Commanding robots with AI chatbots such as ChatGPT and Bard
• Reducing manual effort with automatic data labeling
• Detecting and classifying objects using deep learning for robotics applications
• Motion planning using deep learning for efficient paths in tricky scenarios and faster planning speed
• Controlling robot motion using reinforcement learning
• Deploying deep learning algorithms as CUDA-optimized ROS nodes
Learn more about how to apply AI to enable autonomy in robotics applications: [ Ссылка ]
Related Resources:
• ChatGPT and MATLAB: [ Ссылка ]
• MATLAB and Simulink for Robotics and Autonomous Systems: [ Ссылка ]
• Motion Planning eBook: [ Ссылка ]
• MatGPT - MATLAB app and class to access ChatGPT API from OpenAI: [ Ссылка ]
• Free self-paced online courses about AI: [ Ссылка ]
About the presenters:
Mihir Acharya is a Senior Product Manager for Robotics and Autonomous Systems applications at MathWorks. He’s a specialist in providing solutions for ground vehicles and UAV navigation. Acharya also authors MathWorks’ Autonomous Systems blog to share the latest advancements with the community. Prior to MathWorks, he worked at ABB Corporate Research where he designed robot end effectors, and at Omron Robotics, where he developed path-planning applications for mobile robots. Acharya holds an M.S. in Robotics Engineering from Worcester Polytechnic Institute.
Jose Avendano is a Senior Robotics engineer from MathWorks specialized in robotics research and education. Other previous experience includes modeling, simulation, and algorithm development for robot manipulators, autonomous rendezvous and collaboration for zero-gravity navigation, and robust sensing and control of flexible vehicle structures.
