Exploring Robots are cool. Robots that map their surroundings? Even cooler. But there’s a massive difference between slapping together a chassis and motors and actually building a robot that can autonomously explore and create a map of its environment. That’s the problem I’m setting out to tackle with Minone, my MVP (Minimum Viable Prototype) for an exploration-focused robot.
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| Minone - MVP for SLAM |
Why Start Simple?
Most SLAM (Simultaneous Localization and Mapping) discussions dive straight into complex sensor suites—LiDAR, stereo cameras, high-end IMUs—but I’m deliberately taking the opposite approach. Instead of relying on fancy hardware, Minone is built to push the limits of simple sensors, starting with nothing more than an ultrasonic distance sensor (HC-SR04).
Why? Because understanding SLAM at its core—filtering noisy sensor data, estimating position, and reconstructing an environment—is much more valuable than just plugging in a high-end sensor and hoping for magic. I want to see how much useful data I can extract from the bare minimum before moving on to more advanced solutions.
A Scrap Yard Robot
In true MVP fashion, I built Minone from whatever I had lying around:
- Chassis: The top of an old wine box. (Recycling counts as engineering, right?)
- Motors: Two Roomba drive motors salvaged from an old unit.
- Caster Wheel: From a trashed suitcase. (Turns out, old luggage makes for decent robot parts.)
It’s the ultimate scrap yard robot, which makes it easy to modify as I iterate. That’s already proving useful, since I’m starting to regret my choice of a trailing caster wheel—turning is fine, but the bot has a tendency to tip forward. A problem for Future Me to solve.
Electronics & Control
For brains and motion control, I’m using:
- Microcontroller: ESP-32S
- Motor Driver: L298N H-Bridge
This will be my first time working with an ESP-32S, so I’m looking forward to seeing how it handles real-time sensor inputs and motor control. The L298N should manage the Roomba motors' voltage needs just fine (in theory, at least).
The Underpowered Sensor Challenge
The HC-SR04 ultrasonic sensor is laughably weak for proper SLAM. It’s low-resolution, has a narrow field of view, and struggles with certain surfaces. But that’s exactly why I’m using it—I want to figure out how to make the most of bad data.
If I can extract meaningful spatial information from this absolute potato of a sensor, then adding better sensors later (IR, TOF, LiDAR) will only make the system stronger.
What’s Next?
With the basic hardware in place, the next steps will be:
- Getting Minone moving – Setting up basic motor control with the ESP-32S and L298N.
- Reading sensor data – Making sure the HC-SR04 is providing usable distance measurements.
- Starting simple SLAM tests – Even basic dead reckoning will be a good first step.
As I build and test, I’ll be refining Minone’s design—possibly rethinking that caster wheel before it faceplants one too many times.
Stay tuned for the next update! 🚀
