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Eight units that follow the loop every robot runs: sense, model, decide, act. Each ends in a build.

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Build robots that sense, plan and act.
Take them from the mathematics up, through simulation and onto hardware.

Build robots that sense, plan and act. Kinematics, control, state estimation, perception, navigation and learning, from the mathematics up, in simulation and on hardware.

8 Units

6 Build projects

ROS 2 Core framework

Robotics Engineering Bootcamp

A robot is a mathematical model with a body. This bootcamp starts where the hard part starts, with the geometry of motion, the physics of actuation and the probability of sensing, and builds from there through control, perception, planning and learning, until you can put a working machine into the world and explain why it works.

You work in the stack the field works in: ROS 2, Python and C++, physics simulators, and real sensors and actuators. Every unit ends in something that moves, an arm that reaches, a mobile robot that maps and navigates, a policy trained in simulation that holds up outside it.

It is written for engineers and technical graduates moving into robotics, and for software and machine learning practitioners whose models now have to act on the physical world. Python and first-year mathematics are the starting point; the first unit refreshes the rest.

Curriculum Summary

Kinematics

Dynamics

Control Theory

State Estimation

Sensor Fusion

Computer Vision

SLAM

Motion Planning

Manipulation

Reinforcement Learning

Sim-to-Real

ROS 2

Safety and Testing

Learn. Build. Launch.

Simulation-first labs

Every unit has a lab in a physics simulator, so you can break things freely, and repeatedly, before you touch hardware.

Six build projects

Each unit's work accumulates into projects you can run, show and explain, ending in a capstone robot system.

The industry stack

ROS 2, Python and C++, URDF, physics simulators and standard sensor interfaces, the tools robotics teams already use.

A path to hardware

The later units move from simulation onto real sensors and actuators, with the debugging habits that make the move survivable.

Self-paced, with structure

Study around work and life. Each unit has a clear scope, a lab and a deliverable, so progress is always visible.

AI study assistants

Round-the-clock help from the Academy's AI study assistants, for the mathematics, the code and the debugging.

Master the Robotics Stack

ROS 2, Python and C++, URDF, physics simulators and standard sensor interfaces, the tools robotics teams already use.

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Build Working Machines That Show What You Can Do

Each project is a working robot, or a piece of one, built in simulation and carried toward hardware.

Pick-and-Place Arm

Self-Tuning Motor Controller

Sensor-Fusion State Estimator

Mobile Robot That Maps and Navigates

Learned Grasping Policy

Capstone: Autonomous Robot System

By completing our Bootcamp, you'll obtain the expertise required to thrive in robotics engineering roles.

Every unit ends in something you build. You leave with projects you can run, show and explain, and the understanding to take on what comes next.

Startups

Enterprises

Organizations

The bootcamp prepares you for roles where robots are designed, tuned and put to work.

Robotics Engineer

Design, build and integrate robotic systems, from the mechanism and sensing to the software that ties them together.

Robotics Software Engineer

Write the perception, planning and control software that runs on the robot, usually in ROS 2, C++ and Python.

Controls Engineer

Design and tune the feedback loops that make machines move accurately, safely and efficiently.

Perception Engineer

Build the vision and sensing pipelines that let robots understand the space around them.

05
‍

Mechatronics Engineer

Work across mechanics, electronics and software to bring a machine from concept to a working product.

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Unit 1

The Mathematics of Motion

Every robot is described in coordinates before it is described in code. This unit builds the language the rest of the bootcamp is written in.

Linear Algebra

Rotations and Quaternions

Homogeneous Transforms

Everything is implemented as you learn it, in Python with NumPy and SciPy, so the mathematics is something you run and not something you recite.

Core Overview

You work through coordinate frames, rotations and rigid-body transforms, the calculus of motion, and the physics of force and torque. Rotations get particular care: Euler angles, rotation matrices and quaternions each fail in their own way, and knowing how they fail is what keeps a robot from turning the wrong way at the wrong moment.

Foundation

Linear Algebra

Rotations and Quaternions

Homogeneous Transforms

Rigid-Body Dynamics

Lagrangian Mechanics

Probability Review

Numerical Methods

Scientific Python

Unit 2

Kinematics and Manipulation

How a chain of joints turns into the motion of a hand, and how to ask for the motion you want.

Forward Kinematics

Inverse Kinematics

Jacobians

By the end you can take an arm you have never seen, read its description, and make it do something useful.

Core Overview

Forward and inverse kinematics, Jacobians and what they say about speed and force, singularities, and the shape of a robot's workspace. You describe robots in URDF, plan trajectories through joint space and Cartesian space, and watch a six-joint arm reach, fail and reach again in simulation.

Foundation

Forward Kinematics

Inverse Kinematics

Jacobians

Singularities

Workspace Analysis

Trajectory Generation

URDF and Robot Models

Grasp Basics

Unit 3

Control

Feedback is what lets an imperfect machine do a precise thing.

PID Control

State-Space Models

Stability Analysis

Actuators are part of the story: DC and brushless motors, drivers, encoders, and the limits they put on what a controller can ask for.

Core Overview

From PID tuning to state-space design, LQR and model predictive control. You learn to reason about stability, delay and saturation, to identify a system from data, and to tell a controller that works in simulation from one that will survive contact with a real motor.

Foundation

PID Control

State-Space Models

Stability Analysis

LQR

Model Predictive Control

System Identification

Motors and Drivers

Encoders

Trajectory Tracking

Unit 4

Sensing and State Estimation

A robot never knows where it is. It holds a belief, and the work is making that belief honest.

IMUs

LiDAR

Depth Cameras

The unit closes with a fused state estimator running on recorded and live data.

Core Overview

Inertial sensors, wheel and joint encoders, LiDAR, cameras and depth sensors, each with its own noise and its own way of lying. You model that noise, calibrate against it, and combine sensors with Kalman filters, extended Kalman filters and particle filters.

Foundation

IMUs

LiDAR

Depth Cameras

Sensor Noise Models

Calibration

Kalman Filters

Extended Kalman Filters

Particle Filters

Sensor Fusion

Unit 5

Perception

Turning pixels and point clouds into objects a robot can act on.

Camera Models

Calibration

Feature Matching

Everything is evaluated the way robots are evaluated: on the objects and lighting you did not train on.

Core Overview

Camera models and calibration, feature detection and matching, object detection and segmentation with deep networks, 6-DoF pose estimation and point-cloud processing. You learn where learned perception is strong, where classical geometry is still better, and how to combine the two.

Foundation

Camera Models

Calibration

Feature Matching

Object Detection

Segmentation

Pose Estimation

Point Clouds

Depth Estimation

3D Reconstruction

Unit 6

Mapping and Navigation

Building a map while using it, and getting from one place to another without hitting anything.

Occupancy Grids

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LiDAR SLAM

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Visual SLAM

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The mobile robot you build in this unit maps a room it has never seen and drives to a goal inside it.

Core Overview

Occupancy grids, LiDAR and visual SLAM, localisation against a known map, and the planners that sit on top: A*, RRT, trajectory optimisation and local obstacle avoidance. You run the ROS 2 navigation stack, then open it up to see what each part is doing.

Foundation

Occupancy Grids

LiDAR SLAM

Visual SLAM

Localisation

A* Search

Sampling-Based Planning

Trajectory Optimisation

Obstacle Avoidance

Nav2

Unit 7

Learning for Robots

Where machine learning earns its place in a robot, and where it does not.

Imitation Learning

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Reinforcement Learning

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Policy Gradients

You also meet vision-language-action models, and learn what it takes to run one on a robot rather than on a slide.

Core Overview

Imitation learning, reinforcement learning and policy gradients, applied to manipulation and locomotion. You train in simulation, then spend most of the unit on the gap between simulation and the world: domain randomisation, system identification and the evaluation habits that keep a learned policy honest.

Foundation

Imitation Learning

Reinforcement Learning

Policy Gradients

Simulation Environments

Domain Randomisation

Sim-to-Real Transfer

Vision-Language-Action Models

Evaluation

Unit 8

Systems, Safety and Deployment

A robot is a distributed system with consequences. This unit is about making it dependable.

ROS 2 Architecture

Real-Time Systems

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Hardware Integration

The capstone brings every unit together: a complete robot system, specified, built, tested and presented.

Core Overview

ROS 2 architecture, nodes, messages and timing; real-time constraints; embedded deployment and hardware integration; logging, fault detection and recovery. You study how functional safety is approached in industrial and service robots, and how to test a robot before it is allowed near people.

Foundation

ROS 2 Architecture

Real-Time Systems

Hardware Integration

Fault Detection

Logging and Telemetry

Functional Safety

Testing and Validation

Field Operations

Master Robotics From the Mathematics Up with Our Robotics Engineering Bootcamp

Build robots that sense, plan and act. Kinematics, control, perception and learning, taken from the mathematics up and finished in simulation and on hardware.

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Robotics Engineering Bootcamp

Revolution inspiring a new generation of global AI leaders

Build robots that sense, plan and act. Take them from the mathematics up, through simulation and onto hardware.

Learn. Build. Launch.

Real stories from teams who transformed with LunarTech.

Build Working Machines That Show What You Can Do

By completing our Bootcamp, you'll obtain the expertise required to thrive in robotics engineering roles.

Robotics Engineer

Robotics Software Engineer

Controls Engineer

Perception Engineer

Mechatronics Engineer

LUNARTECH Revolutionizes

In a rapidly changing technological landscape, LunarTech partners with industry leaders to bring to you most cutting edge and innovative solutions.

From $5,997

Unit 1

The Mathematics of Motion

Unit 2

Kinematics and Manipulation

Unit 3

Control

Unit 4

Sensing and State Estimation

Unit 5

Perception

Unit 6

Mapping and Navigation

Unit 7

Learning for Robots

Unit 8

Systems, Safety and Deployment

Revolution inspiring a new
generation of global AI leaders

Build robots that sense, plan and act.
Take them from the mathematics up, through simulation and onto hardware.

Real stories from teams who
transformed with LunarTech.