Physical AI for Robotics and Automation Training Course

This instructor-led, live training in India (online or onsite) is tailored for intermediate-level participants interested in exploring the role of collaborative robots (cobots) and other human-centric AI systems in modern workplaces.

By the end of this training, participants will be able to:

• Understand the principles of Human-Centric Physical AI and its applications.
• Explore the role of collaborative robots in enhancing workplace productivity.
• Identify and address challenges in human-machine interactions.
• Design workflows that optimize collaboration between humans and AI-driven systems.
• Promote a culture of innovation and adaptability in AI-integrated workplaces.

This practical training in India focuses on ROS-PLC integration and digital twins within the context of industrial automation. Learners will master the synchronization of robotic systems with PLCs, create digital replicas for simulation, and enhance production workflows through real-time data exchange and sophisticated monitoring techniques.

This instructor-led, live training in India (online or onsite) is designed for engineers who wish to learn about the applicability of artificial intelligence to mechatronic systems.

By the end of this training, participants will be able to:

• Gain a comprehensive overview of artificial intelligence, machine learning, and computational intelligence.
• Grasp the concepts of neural networks and various learning methodologies.
• Select appropriate artificial intelligence approaches for addressing real-world problems.
• Implement AI applications within the field of mechatronic engineering.

This instructor-led, live training in India (online or onsite) targets advanced robotics engineers and AI researchers seeking to apply Multimodal AI. The objective is to merge various sensory data streams to construct robots that are more autonomous and efficient, possessing the ability to see, hear, and touch.

By the conclusion of this training, participants will be able to:

• Implement multimodal sensing in robotic systems.
• Develop AI algorithms for sensor fusion and decision-making.
• Create robots that can perform complex tasks in dynamic environments.
• Address challenges in real-time data processing and actuation.

An advanced training on India focusing on deep learning for robotic manipulation. Master perception, grasp planning, and control using neural networks and ROS 2. Practical simulation exercises prepare you to effectively deploy intelligent, adaptable grasping solutions on real-world robotic arms.