Robotics with Embedded AI
Durations -15 days.
Program Structure
Modules
- Introduction to Robotics Architecture and Safety Measures
- Low-Level Embedded Systems and Control for Robotics
- Sensors, Perception, and Embedded AI for Robotics
- Motion Control, Actuation, and Robot Locomotion
- Connectivity, IoT, and Cloud Integration for Robotics
- Robotics Safety, Standards, Testing, and Compliance
Experiential Project Based Learning
- Robotic Dashboard System
- AI Vision Robot
- Autonomous Navigation Robot
- IoT-enabled Robot Fleet
- Capstone: Fully Integrated Embedded AI Robot
Program Outcomes
Upon completion, students will have:
- Strong foundation in robotics & embedded systems
- Hands-on experience with Embedded AI
- Ability to design autonomous robotic systems
- Industry-ready portfolio projects
- Skills aligned with Robotics, AI & Embedded job roles
Tools / Platform:
- ESP32, Arduino IDE / ESP-IDF, FreeRTOS
- Python, C/C++
- OpenCV, TensorFlow Lite, Edge AI
- MATLAB / Simulink (control & kinematics)
- ROS concepts, MQTT, Cloud Dashboards
- Sensors: IMU, LiDAR (simulated), Ultrasonic, Camera
- Protocols: UART, I2C, SPI, CAN
Introduction to Robotics Architecture & Safety
Robotics Architecture Fundamentals
Theory
| Evolution of robotics: industrial → service → AI | Robot subsystems: sensing, control, actuation, power, intelligence | Embedded vs PC-based robotic control |
Simulation Activity
| MATLAB/Simulink: basic robotic block diagram | Control loop visualization (sensor → controller → actuator) |
Robotics Safety & Compliance
Theory
| Robot safety standards (ISO 10218 basics) | Emergency stop, safe torque off, collision avoidance | Human–Robot Interaction (HRI) safety |
Virtual Safety Training
| Fault scenarios and emergency handling simulation |
ESP32 Introduction for Robotics
Theory
| ESP32 architecture for robotic systems | FreeRTOS tasks for real-time robot control |
