Course Overview

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.