Intelligent Mechatronics Systems: Robotics, AI & Sensor Fusion

Event Glimpse

The Intelligent Mechatronics Systems: Robotics, AI & Sensor Fusion programme at Acharya Institute of Technology provided hands-on training in intelligent robotics using ESP32, AI/ML, YOLO object detection, sensor fusion, and ROS-based SLAM. Participants progressed from embedded basics to advanced applications, including face recognition, gesture detection, anomaly detection, and predictive maintenance, strengthening practical robotics skills.

About the Program

This program delivers practical training in building intelligent robotic systems, integrating ESP32 embedded hardware with AI/ML techniques like YOLO object detection, sensor fusion, and ROS-based SLAM. Participants progress from basics (LED control, data acquisition) to advanced applications (real-time face/gesture recognition, anomaly detection, predictive maintenance)

Objectives of the Program

• Introduce core concepts of robotics (sensors, actuators, controllers), embedded systems (ESP32, Arduino), and AI/ML fundamentals (classification, regression, vision, motion control) to enable system design.
• Develop proficiency in hardware-software integration, including ESP32 GPIO, sensors (ultrasonic, IR, temperature), actuators (servos, DC motors), and data protocols.
• Teach data acquisition, pre-processing, annotation, and visualization using Python libraries (NumPy, Pandas, Matplotlib, OpenCV) for sensor and IP Webcam streams.
• Cover AI applications: supervised/deep learning, YOLO object detection, reinforcement learning for navigation, face/gesture recognition, anomaly detection, predictive maintenance, and ROS-based SLAM with LiDAR/odometry.
• Foster skills in sensor fusion, multi-model learning, real-time processing, and prototyping via mini-projects, challenges, and a final hackathon-style project.

Expected Outcomes of the Program

• Assemble and program ESP32-based systems for sensor-actuator control, data logging, and real-time visualization, demonstrating LED/sensor projects.
• Collect, label, pre-process, and analyse multimodal data (sensors, video) for ML readiness, including noise removal, normalization, and feature extraction.
• Implement AI models for robotic tasks: real-time object/face detection (YOLO), gesture recognition, autonomous navigation (RL), and SLAM (ROS/LiDAR).
• Integrate multi-sensor fusion (encoders, odometry) for anomaly detection, predictive maintenance, and intelligent decision-making in mechatronic systems.
• Design, prototype, and present a complete intelligent mechatronics project (e.g., sensor-fused robotic application), ready for hackathon competition or industry deployment.