Robotics software for Automation
Robotics Software is a field that focuses on designing, building, and programming robots to perform tasks automatically in industrial and real-world environments.
What is robotics software used for?
It is used to control, automate, and coordinate the operation of robots in industrial and production environments.
It enables tasks such as automated assembly, material handling, navigation, and interaction with machines and systems.
Robotics software helps improve efficiency, reduce manual work, and ensure consistent and repeatable processes.
Modern robotics software integrates with sensors, computer vision, and AI models to give robots the ability to perceive and react to their environment in real time. This makes it possible to handle complex, dynamic tasks that go beyond simple repetition - from object detection and path planning to collaborative work alongside human operators. As a result, companies can deploy robotic systems that adapt to changing conditions and scale alongside their operations.
How do we build robotics software?
We build such software by developing control systems, perception modules, and integrations with hardware and existing infrastructure.
The process includes defining system requirements, implementing control logic, integrating sensors and computer vision, and testing performance in real-world conditions.
Projects typically start with an MVP and are then scaled into production-ready systems designed for reliability and continuous operation.
Throughout the development process, we work closely with hardware teams to ensure that software and physical components operate as a unified system. We use frameworks such as ROS and apply rigorous validation to verify performance under real operational conditions. Our goal is to deliver robotics software that is not only functional on day one, but maintainable, adaptable, and ready to evolve as requirements change over time.
Robotics Implementation Process
Requirements analysis and solution concept
We define the robot’s tasks, operating environment, level of autonomy, and requirements for precision, safety, and interaction.
Output: system concept and functional requirements.
Mechanical design and prototyping
We design the robot structure and select mechanical components such as actuators, transmissions, and materials, building a working prototype.
Output: functional robotic prototype.
Sensor and actuator selection
We select sensors (e.g. cameras, LiDAR, force sensors) and actuators (e.g. motors, servos) to enable perception and interaction with the environment.
Output: hardware setup for sensing and actuation.
Control software and intelligence
We develop control software, including motion control, system logic, and algorithms for perception and decision-making (e.g. AI, SLAM, computer vision).
Output: robot control system.
Testing, simulation, and validation
We test the system in simulation and real-world conditions, validating performance, accuracy, and safety.
Output: validated system ready for deployment.
Integration and system maintenance
We integrate the robot into the client’s environment (e.g. production lines, IT systems) and continuously monitor and improve performance.
Output: reliable and scalable robotic system.
Case study
Coco
Coco robotic delivery is a leading delivery service that deploys remotely piloted sidewalk vehicles to make last-mile deliveries more affordable, reliable, and sustainable.
With xBerry’s support and collaboration, Coco has achieved significant improvements in the reliability and performance of their onboard software stack.
Maddie Robot
Maddie is a conceptual robot designed to perform mosaic household tasks – from bringing water from the fridge to vacuuming and arranging a phone call.
Using several advanced techniques, from complex image and data processing to expansion algorithms, we built an innovative prototype that allowed us to move into the future of fully functional household robots.
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