At the core of every arculee, our Autonomous Mobile Robot (AMR) is its brain. This powerful software system processes sensor data, executes commands, and guides the robot through complex environments. Software Engineer Thomas Fuhrmann explains how it works and why it’s essential to the robot’s performance.
What is the arculee Brain?
The brain is the central software of an arculee that manages all the tasks of the robot, including navigation, decision-making, and command execution. It receives orders from an outside source, like a fleet manager, processes its surroundings through sensor data, decides movements, and ensures overall efficiency in AMR operations.
Thomas Fuhrmann, Software Engineer at arculus, uses the analogy of the human brain to clarify its functions:
"The arculee brain functions similarly to a human brain. If you imagine an arculee as a body, the chassis is like the physical form; the electronics and cable harnesses are the organs and blood vessels. Just like in humans, the brain controls everything for the robot."
Processing the environment
Thomas highlights three main steps the arculee brain follows when processing its surroundings:
- Sensing: The arculee uses different sensors to gather information about its environment, similar to how humans rely on sight or hearing. For example, sensors like LiDAR generate detailed point clouds that map the robot’s surroundings.
- Interpreting: The brain processes the sensor data to interpret the real world. For instance, it can locate itself and recognise objects and obstacles that might be present in the robot’s path.
- Implementing: Based on the interpretation, the robot makes timely decisions, such as stopping or altering its route to avoid collision with an object in the way.
The Brain’s Tech Stack
Developers at arculus build the arculee brain entirely in-house and avoid relying on external frameworks to maintain full control over performance and system behaviour. Thomas explains that they use C++ for the core system because it provides the speed and low-level access required for efficient robotics. For user interface components, they use Python, which allows for faster development and more efficient testing.
To improve modularity and efficiency, the developers plan to migrate the stack to ROS2, a well-known robotics framework that enables clearer system architecture and easier integration of new components. We will explore this migration in a future blog post.
Challenges and Solutions
Developing a sophisticated piece of technology like the arculee brain comes with its own set of challenges. Thomas points out the following three:
- Code Maintenance: The brain stack, including the code base, has evolved over the years, becoming increasingly complex. As features and functionalities expanded, maintaining the code became more challenging due to increased interdependencies within the program and legacy structures. The team tackles this by constantly checking and conducting frequent debugging sessions.
- Managing Complexity: Our AMRs navigate autonomously in dynamic environments. This requires a solid system that can handle a wide range of possible scenarios and corner cases for maximum efficiency, safety, and optimal performance.
- Testing and Validation: The office testing area allows developers to test the arculees in a controlled environment to ensure quality before deployment. However, the robots don’t always behave as expected, especially during the early stages of development. To improve performance and stability, the team runs countless tests and refines the software based on real-world behaviour.
Sharper Brain, Stronger arculees
The arculee brain handles all the core functions of the robot and can thus make or break it. Thomas sees a well-designed brain as key to precision, reliability, and adaptability. As development continues, improvements in navigation and decision-making will help arculees respond more effectively to increasingly complex environments. A sharp brain doesn’t just keep an AMR moving—it sets the foundation for smarter automation.
