Visual SLAM Indoor Mapping Robot
Indoor Mapping Robot Kit – Build a 2D Occupancy Grid with RPLidar A1 and OpenCV SLAM
Every part needed, pre-tested for compatibility, with an AI build companion trained on this exact project. Shipped from Bengaluru in 3-5 days.
This kit lets you build a wheeled robot that autonomously explores and maps unknown indoor spaces, generating a 2D occupancy grid in real time. From warehouse automation prototypes to academic SLAM research, you'll assemble a system where lidar scans and high-speed odometry fuse to create a reliable map. The RPLidar A1 delivers 360-degree distance readings while the STM32 microcontroller runs a PID loop on encoder feedback, ensuring the robot’s motion is tracked with millimetre accuracy.
What You'll Build
You will construct a differential-drive robot powered by a 12V SLA battery and controlled by an Arduino UNO Q that communicates with a Linux host for heavy computation. The robot uses the RPLidar A1 to capture laser scans and OpenCV algorithms on the Linux side to stitch those scans into a coherent occupancy grid. Enclosed in a custom prototype-board chassis, the final platform navigates around obstacles and localises itself without external beacons – a self-contained mapping machine ready for algorithm development.
What You'll Learn
- Sensor fusion combining lidar range data and encoder ticks for robust, drift-free odometry
- Implementing a high-speed PID control loop on STM32 for precise DC motor regulation
- Building and parameterising a 2D SLAM pipeline using RPLidar A1 and OpenCV on Linux
- Integrating a real-time microcontroller with a single-board computer for split processing architectures
Kit Contents
| Component | Quantity |
|---|---|
| Arduino UNO Q | 1 |
| RPLidar A1 | 1 |
| LM393 Encoder | 2 |
| L298N Driver | 1 |
| DC Geared Motor 12V | 2 |
| LM2596 Buck Converter | 2 |
| 12V 5Ah SLA Battery | 1 |
| XT60 Connector | 1 |
| 100nF Caps | 10 |
| PCB Prototype Board | 3 |
| USB-C Hub | 1 |
| Soldering Iron | 1 |
| Solder Wire | 1 |
Why Buy This Kit Instead of Sourcing Parts Separately
| Factor | Sourcing Separately | Compoden Kit |
|---|---|---|
| Compatibility checks | You verify every part | Pre-tested as a system |
| Build support | Forums and scattered tutorials | AI companion trained on this exact project |
| Time to first working build | Days of debugging | Hours, with step-by-step guidance |
| Shipping coordination | Multiple sellers, multiple delays | One shipment from Bengaluru in 3-5 days |
Who This Kit Is For
Designed for engineering undergraduates and postgraduates in ECE, EEE, or Mechanical streams at institutions like IITs, NITs, VIT, and BITS Pilani who are diving into SLAM and autonomous systems. It’s equally suited for Smart India Hackathon teams building indoor mapping prototypes and for research scholars validating sensor fusion algorithms. A solid footing in Linux, C++ basics, and an eagerness to work with real-time hardware is expected.
Built and Backed by Compoden
Every Compoden kit ships with an AI build companion trained on this exact project — accessible via a QR code on the box, with WhatsApp and email backup. We've spent 10 years building projects for makers, schools, and institutions across India. If a part fails because of a manufacturing defect, replace it free within 7 days.
What if I get stuck during the build?
Scan the QR code to launch the AI companion, which walks you through calibration, wiring, and code deployment step by step. For complex debugging, message us on WhatsApp with photos of your setup.
Does this kit include a camera for visual SLAM?
The SLAM pipeline primarily uses the RPLidar A1; however, OpenCV is ready for visual features. You can connect any USB webcam to the Linux host and our companion will guide you through extending the map with visual data.
What prior knowledge is required?
You should be comfortable working with the Linux command line, have basic C++ experience for STM32 firmware, and understand concepts like ROS topics. The companion explains the SLAM maths in detail.
Can this robot map a multi-storey building?
The kit performs 2D occupancy grid mapping on a single floor. For multi-floor mapping, you would need an IMU or barometer, which our AI companion can help you integrate as a custom extension.
RPLidar A1 + OpenCV on Linux builds 2D occupancy grid. STM32 runs real-time wheel encoder odometry PID.
What's in this kit
Choose your assembly option:
- Soldering Kit — 25W soldering iron, 60/40 solder wire, flux, and small perfboard for permanent assembly.
- Breadboard Combo — 800-point full-size breadboard with 65-piece jumper wire pack for solderless prototyping.
Shipping Information
- Prepaid Orders: ₹75 for orders up to ₹999, FREE shipping above ₹999
- COD Orders: ₹125 shipping + ₹50 COD fee = ₹175 total
- Delivery Timeline: Dispatch in 1-2 days, delivery in 2-7 days depending on location
Returns & Warranty
- 7-Day Return: Manufacturing defects only (approval required)
- Warranty: 7 days from delivery
- Non-Returnable: Batteries, consumables, cut wires, clearance items