Self-driving vehicle software and Artificial Intelligence

Self-driving vehicle software uses artificial intelligence (AI) and machine learning algorithms to enable vehicles to operate autonomously, without the need for human intervention. Here are some ways AI can be used in self-driving vehicle software:

  1. Computer vision: AI-powered cameras and sensors can be used to detect objects and obstacles in the environment around the vehicle, allowing it to navigate through complex environments such as urban streets and highways.

  2. Route planning: AI can be used to plan the most efficient route for the vehicle based on factors such as traffic conditions and road closures.

  3. Predictive maintenance: AI can monitor the vehicle’s performance and predict when maintenance is needed, reducing downtime and increasing efficiency.

  4. Natural language processing: AI can be used to understand and respond to voice commands from passengers, making the vehicle more user-friendly.

  5. Real-time monitoring: AI can monitor vehicle performance in real-time, allowing for adjustments to speed, direction, and other variables to optimize safety and efficiency.

  6. Data analysis: AI can analyze data collected from sensors and cameras to provide insights into traffic patterns, weather conditions, and other factors that may impact vehicle operation.

Modular and flexible AGV

A flexible AGV, or autonomous guided vehicle, is a type of mobile robot that can adapt to a variety of tasks and environments without requiring significant reprogramming or physical modifications. These AGVs are designed to be versatile and adaptable, allowing them to be quickly reconfigured or redeployed to meet changing needs.

There are a number of different features that can make an AGV more flexible. For example, some AGVs are designed with modular components that can be easily swapped out or upgraded to adapt to different tasks. Others may use sensors and machine learning algorithms to adapt to changing environments and avoid obstacles or hazards.

In addition, flexible AGVs may be designed to work with a variety of different payloads or to operate in different types of environments. For example, some AGVs may be designed to work in warehouses or manufacturing facilities, while others may be used in hospitals or laboratories.

We have considerable experience in mechatronic prototyping in particular in the prototyping of self-driving vehicles.

Logirobotix engineers develop self-driving small vehicles software. Vehicles are automatically controlled through a camera or lidar. Such low-cost AGVs are based on an economical trolley and engines. In the 21st century, Automated Guided Vehicle (AGV) is used in almost all industries, such as factory assembly, food delivery, inventory control, and general manufacturing. For many industries, AGV has become an indispensable part of the auditing process.

Brushless motors

A brushless motor is a type of electric motor that uses electronic commutation instead of brushes to control the movement of the motor. These motors are commonly used in autonomous guided vehicles (AGVs) because they offer a number of advantages over other types of motors.

One major advantage of brushless motors is their high efficiency. Because there are no brushes to create friction, the motor is able to operate more efficiently and generate less heat. This can result in longer battery life for the AGV and increased overall performance.

Another advantage of brushless motors is their low maintenance requirements. Because there are no brushes to wear out, there is less need for regular maintenance or replacement of parts. This can result in lower costs over the lifetime of the AGV.

Finally, brushless motors offer precise control over speed and torque, which can be important in AGV applications where precise movement and positioning is required. These motors can be easily programmed and controlled using electronic controllers, which allows for a high degree of accuracy and repeatability.

Recent developments in small but powerful brushless motors have opened up the possibility of a highly maneuverable and cost-effective solution for robotics. Although these motors are made for consumer applications, they are equipped with Hall sensors, capable of delivering high torque.
These motors are designed to withstand the brutal use of skateboarders and therefore can be expected to perform very reliably in the use of AGVs. Logirobotix uses one of these very economical motors in an innovative way to provide both thrust and steering.

agv based on modular structure

Self driving and AI

Unfortunately, the high cost and complexity of many AGVs have precluded their use in many smaller industries that could greatly benefit from their use.

To address this important problem, we have developed a very low-cost AGV. This robot is ideal for transporting light materials such as food, linen, or medicines in hospitals.

Low cost AGV

The development of an inexpensive AGV truck – less than 2000 Euro, but high performing, for small businesses and light industry, allows for almost unlimited applications.

Low-cost AGVs, or autonomous guided vehicles, are mobile robots designed to be affordable and accessible to a wide range of businesses and industries. There are several factors that contribute to the cost of an AGV, including the type of vehicle, the sensors and navigation system used, and the complexity of the programming.

Here are some ways to create a low-cost AGV:

  1. Use a simple design: Simplifying the design of the AGV can help reduce the overall cost. For example, a basic platform with four wheels and a single motor can be used instead of more complex designs.

  2. Use low-cost sensors: Rather than using expensive sensors, consider using low-cost alternatives that are still capable of performing the required tasks. For example, infrared sensors or ultrasonic sensors can be used for obstacle avoidance.

  3. Use a basic navigation system: A basic navigation system can be used to guide the AGV around the facility. For example, a simple magnetic tape or optical sensor system can be used instead of a more complex laser-guided system.

  4. Use an open-source platform: An open-source platform such as ROS (Robot Operating System) can be used to develop the software for the AGV. This can help reduce the development costs and allow for greater flexibility in the programming.

prototype self driving vehicle agv
AI autonomous vehicle


The proposed navigation is through Lidar or line-following.


Traditional AGVs / robots are only available in limited sizes. Our robot is available in any size up to 1510mm.

Easy implementation

The robot does not need additional IT infrastructure and a single robot deployment can be completed in 2 hours.

Modular solution

In traditional AGV implementations, the AGV and the cart are separate, which can cause integration problems. In our robot, the trolley and the AGV are within a single platform.