It can be both exciting and intimidating to begin a robotics journey. With so many components available, it’s easy to feel overwhelmed and assume you need expensive parts—like powerful onboard computers or high-end LiDAR systems—just to get started. But choosing the wrong components not only wastes money, it can also lead to frustration and poor performance. This guide helps you build your first robot with a smart, affordable robot starter kit designed specifically for beginners.
Buying components that are specifically suited to the problem you’re trying to solve is a fundamental principle that this guide will teach you to help you make better purchasing decisions. When you’re ready to move on to more complex navigation projects, we’ll show you how to build a basic obstacle-avoiding robot and then walk you through the necessary upgrades.
Level 1: The First Robot – The Simple Obstacle Avoider Robot Starter Kit
The Goal: Your first robot will perform a simple task: avoid obstacles in its path. The robot doesn’t need to know where it is or where it’s going. Its only “worldview” is simple: “Is there an obstacle in front of me?” Based on that, the robot will either move forward or change direction.
This is the “Hello World” of mobile robotics, and you should focus on the basics at this stage, ensuring you have the right components for the task.
The Essential “Level 1” Shopping List
We can break down the necessary components by the functions they will serve within the robot.
1. Actuation (How the Robot Moves)
- Components:
- 2x or 4x DC Geared Motors (Without Encoders): These are low-cost, easy-to-control motors. They provide enough power for basic tasks like moving forward or turning.
- Motor Driver (L298N or similar): A motor driver acts as an intermediary between the microcontroller and the motors, ensuring the correct power is sent to the motors based on high-level commands from the robot’s brain.
- 2x or 4x DC Geared Motors (Without Encoders): These are low-cost, easy-to-control motors. They provide enough power for basic tasks like moving forward or turning.
- Why These Parts?
The primary task for a simple obstacle-avoiding robot is motion. You don’t need precision here. You need basic functionality like goForward(), goBackward(), turnLeftForABit(), turnRightForABit(). Therefore, DC motors without encoders are sufficient. Encoders track precise movement and are unnecessary at this stage since you’re not concerned with fine control or distance measurements.
2. Perception (How the Robot Senses)
- Component:
- Ultrasonic Sensor (HC-SR04): This sensor emits sound waves and measures how long it takes for the echo to return. It gives you a single distance reading that tells the robot how far away an obstacle is.
- Ultrasonic Sensor (HC-SR04): This sensor emits sound waves and measures how long it takes for the echo to return. It gives you a single distance reading that tells the robot how far away an obstacle is.
- Why This Part?
The robot’s main task is to detect obstacles in its path and avoid them. The ultrasonic sensor is ideal for this. It’s inexpensive, simple to use, and provides just enough data to enable basic decision-making. At this level, you don’t need complex 360-degree sensors because the robot only needs to know if there’s an object in front of it.
3. Foundation (The Body and Brain)
- Components:
- Robot Chassis: A simple acrylic or metal frame to hold all components together.
- Microcontroller (Arduino Uno / ESP32): This is the brain of the robot. It processes inputs from the sensor and sends commands to the motor driver.
- Battery Pack & Power Supply: To power the microcontroller and the motors.
- Robot Chassis: A simple acrylic or metal frame to hold all components together.
This entire kit can be purchased for under $50, and it’s perfectly suited to the problem at hand. At this stage, you’re focusing on learning the basics of motor control and sensor input, not building a high-performance robot.
Level 2: The Upgrade – The Autonomous Warehouse Navigator
The Goal: Once you’ve successfully built and tested the basic obstacle-avoiding robot, it’s time for a more advanced challenge: building a robot capable of mapping its environment, navigating autonomously, and avoiding dynamic obstacles. This is the start of more sophisticated tasks, such as Simultaneous Localization and Mapping (SLAM) and path planning.
At this level, the basic components you used in Level 1 are no longer sufficient. Let’s look at the necessary upgrades.
The Upgraded “Level 2” Shopping List
1. Actuation & Odometry (Precise Movement and Self-Tracking)
- Upgrade From: DC Motors without Encoders
- Upgrade To: DC Motors with Encoders
- Why the Upgrade?
Encoders are disks that attach to the motor shaft and track rotations by counting how many “slots” pass by a sensor. This allows you to measure how far each wheel has turned, enabling the robot to estimate its position and orientation. This data, known as odometry, is essential for SLAM and other navigation tasks. Without it, the robot won’t be able to track its movements accurately, making autonomous navigation impossible.
2. Perception (Comprehensive World Understanding)
- Upgrade From: Ultrasonic Sensor
- Upgrade To: 2D LiDAR (e.g., RPLIDAR A1, YDLIDAR X4)
- Why the Upgrade?
A 2D LiDAR sensor provides a 360-degree view of the robot’s surroundings, giving it access to a large set of data points, rather than just one. This richer data is necessary for creating a detailed map of the environment (SLAM). Unlike ultrasonic sensors, which only measure a single distance at a time, a 2D LiDAR offers continuous, real-time scanning of the environment, crucial for obstacle avoidance and navigation.
3. Localization & Pose Correction (Adding Robustness)
- New Component:Inertial Measurement Unit (IMU)
- An IMU, such as the MPU-6050 or BNO055, measures the robot’s orientation and rotational velocity, helping it detect changes in direction and orientation.
- An IMU, such as the MPU-6050 or BNO055, measures the robot’s orientation and rotational velocity, helping it detect changes in direction and orientation.
- Why Add This?
Odometry data can accumulate errors over time, especially if a wheel slips. The IMU helps correct these errors by providing additional data about the robot’s rotation. This is essential for maintaining an accurate estimate of the robot’s position, which is crucial for successful navigation. ROS navigation stacks, such as Nav2, can fuse the data from the IMU and encoders to improve overall localization accuracy.
| Feature Required | Level 1 Component (Obstacle Avoider) | Level 2 Component (Navigator) | Why the Upgrade is Necessary |
| Crude Motion | DC Motors | – | Sufficient for simple reactions. |
| Precise Motion | – | Motors with Encoders | Essential for odometry to track position for SLAM/navigation. |
| Single-Point Sensing | Ultrasonic Sensor | – | Sufficient for “is there a wall?” check. |
| 360° Environment Sensing | – | 2D LiDAR | Essential for building a map and seeing obstacles from all angles. |
| Rotation Correction | – | IMU | Fuses with encoder data to correct for wheel slip and improve localization accuracy. |
The “Don’t Buy This Yet” List: Why More Isn’t Always Better
As you progress with your robot, you may be tempted to buy high-end components, but it’s important to know when they are unnecessary. More advanced parts are not always better for your specific use case, and they could add unnecessary complexity or cost.
Why Not a 3D LiDAR?
A 3D LiDAR (like the Velodyne Puck) offers a 360-degree point cloud in both horizontal and vertical directions, creating a complete 3D map. However, for a robot navigating a flat surface, such as in a warehouse, a 2D LiDAR is sufficient. The vertical data from a 3D LiDAR is redundant for floor-level tasks, and processing the data requires more power and computational resources.
Why Not a Depth Camera?
Depth cameras, such as Intel RealSense, provide depth information alongside a standard image, but they have limitations:
- Limited Range and Narrow Field of View: They often cannot detect objects at the range of a LiDAR sensor.
- Computational Cost: Processing depth data is more computationally intensive than processing the sparse data from a LiDAR.
- Environmental Sensitivity: Their performance can degrade in poor lighting conditions or with reflective surfaces.
For a robot focused on 2D mapping and navigation, a 2D LiDAR is a more efficient, reliable, and cost-effective solution.
Conclusion: Spend Smartly to Build a Strong Foundation
When building your first robot, focus on buying parts that solve the immediate problem. Start with basic components like DC motors, an ultrasonic sensor, and an Arduino. Once you’ve mastered the fundamentals, it’s time to upgrade your components for more advanced tasks such as mapping, localization, and autonomous navigation.
For more details on working with 2D LiDAR for robot navigation, check out the RPLIDAR A1 datasheet.
By understanding the core functionality you need at each stage and making upgrades when the problem demands them, you’ll avoid unnecessary expenses and build a strong foundation for more advanced robotic systems in the future.
If you’re serious about building real-world robots—from basic obstacle avoiders to autonomous navigation systems—our Mobile Robotics Engineering course at Robotisim offers guided, hands-on learning to help you get there. Learn with expert-curated hardware recommendations, step-by-step tutorials, and project-based lessons built for beginners and hobbyists alike.