Physical AI for Robotics and Automation Training Course

This guided, live training in Kenya (available online or onsite) targets intermediate-level participants interested in exploring the impact of collaborative robots (cobots) and other human-centric AI systems on contemporary workplaces.

Upon completing this training, learners will be equipped to:

• Grasp the core principles of Human-Centric Physical AI and their practical applications.
• Examine how collaborative robots contribute to improved workplace efficiency.
• Recognize and resolve issues arising from human-machine interactions.
• Create workflows that maximize the synergy between humans and AI-driven systems.
• Foster a workplace culture that values innovation and adaptability in AI-integrated environments.

This practical training in Kenya addresses ROS-PLC integration and digital twins within industrial automation. Participants will learn to synchronize robotic systems with PLCs, create digital replicas for simulation purposes, and enhance production workflows through real-time data exchange and sophisticated monitoring techniques.

This instructor-led live training in Kenya (online or onsite) is designed for engineers who want to explore how artificial intelligence can be applied to mechatronic systems.

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

• Obtain an overview of artificial intelligence, machine learning, and computational intelligence.
• Grasp the concepts of neural networks and various learning methods.
• Select the most effective AI approaches for addressing real-world problems.
• Implement AI applications within mechatronic engineering.

This instructor-led, live training in Kenya (online or onsite) is designed for advanced robotics engineers and AI researchers eager to harness Multimodal AI to integrate diverse sensory data, thereby creating robots that are more autonomous, efficient, and capable of seeing, hearing, and touching.

Upon completing this training, participants will be equipped to:

• Implement multimodal sensing within robotic systems.
• Develop AI algorithms for sensor fusion and decision-making processes.
• Build robots capable of executing complex tasks in dynamic environments.
• Tackle challenges associated with real-time data processing and actuation.

This advanced training in Kenya focuses on applying deep learning to robotic manipulation. Participants will explore perception, grasp planning, and control using neural networks and ROS 2. Through practical simulation exercises, you will be prepared to effectively deploy intelligent and adaptable grasping solutions on real robotic arms.