Smart Robotics in Manufacturing: AI for Perception, Planning, and Control

• An understanding of robotic systems and kinematics
• Experience with Python programming
• Familiarity with AI or machine learning concepts

Audience

• Robotics engineers
• Systems integrators
• Automation leads

Smart Robotics is the integration of artificial intelligence into robotic systems for improved perception, decision-making, and autonomous control.

This instructor-led, live training (online or onsite) is aimed at advanced-level robotics engineers, systems integrators, and automation leads who wish to implement AI-driven perception, planning, and control in smart manufacturing environments.

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

• Understand and apply AI techniques for robotic perception and sensor fusion.
• Develop motion planning algorithms for collaborative and industrial robots.
• Deploy learning-based control strategies for real-time decision making.
• Integrate intelligent robotic systems into smart factory workflows.

Format of the Course

• Interactive lecture and discussion.
• Lots of exercises and practice.
• Hands-on implementation in a live-lab environment.

Course Customization Options

• To request a customized training for this course, please contact us to arrange.

Introduction to Smart Robotics and AI Integration

• Overview of robotics in Industry 4.0
• AI’s role in perception, planning, and control
• Software and simulation environments

Perception Systems and Sensor Fusion

• Computer vision for robotics (2D/3D cameras, LiDAR)
• Sensor calibration and fusion techniques
• Object detection and environment mapping

Deep Learning for Perception

• Neural networks for visual recognition
• Using TensorFlow or PyTorch with robotic data
• Training perception models for object tracking

Motion Planning and Path Optimization

• Sampling-based and optimization-based planning
• Working with MoveIt for motion planning
• Collision avoidance and dynamic re-planning

Learning-Based Control Strategies

• Reinforcement learning for robotic control
• Integrating AI into low-level control loops
• Simulation with OpenAI Gym and Gazebo

Collaborative Robots (Cobots) in Smart Manufacturing

• Safety standards and human-robot collaboration
• Programming and integrating cobots with AI
• Adaptive behaviors and real-time responsiveness

System Integration and Deployment

• Interfacing with industrial controllers (PLC, SCADA)
• Edge AI deployment for real-time robotics
• Data logging, monitoring, and troubleshooting

Summary and Next Steps