Course Title: Robotics Software Engineer Program

Level: Beginner to Intermediate

Duration: 6–12 months (flexible, modular)

Details : Mode: Online + Hands-on Labs + Mentorship + Capstone Project

Target Audience:

Aspiring robotics software engineers

AI/ML developers aiming to specialize in robotics

Students & professionals in CS, EE, or Mechatronics

Module 1: Fundamentals of Robotics & Automation

Duration: 3 weeks

Key Topics:

Introduction to Robotics: History, types, and applications

Robotic Kinematics and Dynamics (Forward/Inverse Kinematics)

Degrees of Freedom (DOF), joints, actuators, and sensors

Robotics programming fundamentals

Basic electronics & embedded systems for robotics

Hands-on Labs:

Arduino/Raspberry Pi basics

Controlling motors and actuators

Sensor integration (ultrasonic, IR, LIDAR)

Module 2: Programming for Robotics

Duration: 4 weeks

Key Topics:

Python & C++ for robotics

Data structures, algorithms for robotics control

ROS (Robot Operating System) architecture

Gazebo & V-REP simulation environments

Writing ROS nodes, topics, and services

Hands-on Labs:

ROS installation and basic navigation

Simulated robot control in Gazebo

Sensor data reading and actuation

Module 3: Artificial Intelligence in Robotics

Duration: 5 weeks

Key Topics:

Introduction to AI & Machine Learning in robotics

Computer vision for robotics: OpenCV, object detection, tracking

Deep Learning with TensorFlow/PyTorch for robotics

Reinforcement Learning for autonomous decision making

Path planning algorithms: A*, Dijkstra, RRT

Hands-on Labs:

Object recognition for robot navigation

Implementing RL for obstacle avoidance

Vision-based grasping simulations

Module 4: IoT & Embedded Systems Integration

Duration: 3 weeks

Key Topics:

IoT protocols: MQTT, HTTP, CoAP for robotics

Wireless communication: Bluetooth, ZigBee, Wi-Fi

Real-time data collection from sensors

Edge computing for robotics intelligence

Cloud integration for remote monitoring & control

Hands-on Labs:

Building IoT-enabled robotic arm

Remote monitoring using cloud dashboards

Sensor fusion from multiple sources

Module 5: Advanced Robotics & Industry Applications Duration: 6 weeks

Key Topics:

Autonomous vehicles and drones (UAVs)

Humanoid & service robots programming

Industrial robots and automation solutions

Multi-robot coordination and swarm robotics

Safety standards and testing

Hands-on Labs:

Drone navigation & control

Humanoid robot simulation

Programming collaborative robots (cobots)

Module 6: Robotics Software Engineering Practices

Duration: 2 weeks

Key Topics:

Version control (Git) & collaborative development

Software architecture for robotics applications

Testing & debugging in simulation and real hardware

CI/CD pipelines for robotics software

Deployment & maintenance

Hands-on Labs:

Writing modular, reusable ROS packages

Unit testing & integration testing for robots

Continuous integration for simulation pipelines

Module 7: Capstone Project & Industry Deployment

Duration: 4–6 weeks

Description:

Learners will design, develop, and deploy a full-fledged robotics project integrating AI, IoT, ROS, and sensors. Examples include:

Autonomous warehouse robot

AI-powered delivery drone

Smart robotic arm with vision-guided manipulation

Multi-robot swarm navigation system

Industry Mentorship:

Guidance by robotics engineers & AI specialists

Code review & optimization

Deployment strategies for industrial clients

Outcome:

Capstone project showcase

Industry-ready portfolio

Certificate of Robotics Software Engineering

Optional Specialization Tracks

AI & Vision Robotics – Advanced ML/DL, computer vision for autonomous systems

Industrial Robotics and Automation – PLC, SCADA, industrial IoT integration

Drone and Autonomous Vehicles – UAV control, navigation, swarm coordination

Humanoid and Service Robots – Motion planning, natural interaction, AI behaviors

Tools & Technologies Covered Languages: Python, C++, MATLAB

Robotics Frameworks: ROS, Gazebo, V-REP

AI/ML: TensorFlow, PyTorch, OpenCV

IoT & Cloud: Arduino, Raspberry Pi, MQTT, AWS IoT

Simulation & CAD: SolidWorks, Blender (for robot design)

Key Features – DeepTechKnowledge Style Project-based learning: 70% hands-on, 30% theory

Mentorship: One-on-one guidance from industry experts

Industry exposure: Connect with robotics firms & startups

Portfolio building: Real-world projects for career-ready profiles

Global relevance: Robotics software skills for India and international markets

Career Outcomes

Robotics Software Engineer

AI & Robotics Developer

Autonomous Systems Engineer

IoT and Robotics Integration Specialist

Drone and UAV Software Engineer

Industrial Automation & Robotics Consultant

Certification: Upon successful completion, learners receive a "Certificate in Robotics using Generative AI for DeepTech Innovation", co-issued by DeepTechKnowledge and partnered legal-tech institutions.