Day 1

First Half: Foundations in Next-Gen Robotics & AI

● Workshop Overview & Objectives

● Introduce the vision: building a robotics platform that leverages AI-powered computer vision

for intelligent decision-making.

● Outline the key components: robotics mechanics, electronics integration, AI using YOLO, and

MQTT messaging.

● Robotics & Electronics Essentials

● Core Concepts: Brief review of the essential robotics system (e.g., robotic arm or mobile

robot) and the role of embedded electronics.

● Power & Motor Control: Highlight the key points of integrating BLDC motors (or other

actuators) and electronic speed controllers.

● Introduction to AI & Computer Vision

● Overview of YOLO: Explain the “You Only Look Once” object detection algorithm—its

benefits for real-time applications and relevance in robotics.

● ESP Cam as a Vision Sensor: Introduce the ESP Cam as an affordable, lightweight solution

for capturing live video and running basic vision tasks.

● Fundamentals of MQTT Communication

● MQTT Basics: Outline the publisher–subscriber model and its suitability for lightweight,

real-time messaging between sensors (ESP Cam) and the robot’s control unit.

● Role in Robotics: Discuss how MQTT can facilitate communication for AI-based decision-making and control.

Second Half: Hardware Assembly & Initial Setup

● Robotics Platform Assembly

● Essential Mechanical Setup: Assemble the key structural components of the robotics

platform with an emphasis on mounting locations for sensors and actuators.

● Minimalist Approach: Focus only on the critical structural elements needed to support the

ESP Cam and motion components.

● Electronics Integration

● ESP Cam Installation: Mount and wire the ESP Cam on the robotics platform ensuring an

optimal field of view.

● Basic Wiring & Power Distribution: Connect the ESP Cam and core motor controllers to the

power source, emphasising safe and reliable wiring.

● Initial Programming & MQTT Setup

● ESP Cam Basics: Upload simple code to the ESP Cam for image capture and streaming.

● MQTT Connectivity: Configure the ESP Cam (or an associated microcontroller) to publish

basic status or image metadata to an MQTT broker.

● Demonstration & Troubleshooting: Run initial tests to verify that the ESP Cam streams data

and sends MQTT messages successfully.

Day 2

First Half: Advanced AI Integration with YOLO on ESP Cam

● Deep Dive into YOLO

● Understanding YOLO: Explain the workings of YOLO (or Tiny YOLO for constrained

devices), including network architecture, detection thresholds, and bounding box outputs.

● Adaptations for Embedded Systems: Discuss considerations when deploying YOLO on

resource-constrained devices like the ESP Cam (or interfacing with a nearby processing unit).

● Programming AI on the ESP Cam

● Integrating YOLO: Walk through the process of setting up a YOLO model (or connecting to a

remote server running YOLO) to process live video from the ESP Cam.

● Real-Time Object Detection: Develop code that captures images, runs YOLO for object

detection, and identifies key objects in the scene.

● MQTT-Driven AI Messaging

● Data Packaging: Show how to package YOLO detection results (e.g., object type,

confidence, position) into MQTT messages.

● Publishing Results: Configure the ESP Cam or its companion processor to publish detection

messages to the MQTT broker.

● Hands-On Coding: Participants update and test their code to ensure that AI-based detections

are transmitted in real time via MQTT.

Second Half: System Integration, Testing & Optimisation

● Integrating AI with Robotic Control

● End-to-End Communication: Connect the MQTT messages from the ESP Cam to the main

robotics control unit (e.g., a microcontroller or onboard computer) that will act on the detected

objects.

● Decision-Making Logic: Implement basic logic so that the robot responds to AI detections

(for example, altering its path or activating specific behaviors when an object is detected).

● Testing

● Live Demonstration: Run the robotics platform in a controlled environment where the ESP

Cam performs object detection using YOLO, and MQTT messages drive robotic responses.

● Performance Evaluation: Evaluate response times, detection accuracy, and messaging

reliability.

● Parameter Tuning: Adjust YOLO thresholds, MQTT message frequencies, and control logic

based on testing feedback.

● Wrap-Up & Future Directions

● Final Demonstration: Present a full demonstration of the integrated system where

AI-powered object detection informs robotic actions in real time.

● Discussion & Q&A: Open discussion on challenges, solutions, and potential

applications—ranging from automated navigation to swarm robotics.

● Resources & Next Steps: Provide pointers for further exploration in embedded AI, advanced

MQTT integrations, and scaling up next-gen robotics solutions. 

Lunch is included for 2 Days during the workshop.

Certification

All participants will receive a globally recognised hard-copy Certificate of Participation.

Eligibility:

Open to All, Final Year Students, and learners from any stream:

B.Tech, B.E, M.B.B.S, BCA, MCA, MS, MD, B.Sc IT, M.Sc IT, Biomedical, Bio-Technology, BBA, MBA, B.A, hobbyists and more.