formigas GmbH
About us
ððŒ-ðð¿ð²ð®ðð¶ð»ðŽ ðð»ðð²ð¹ð¹ð¶ðŽð²ð»ð ððððŒðºð®ðð¶ðŒð». As a development partner, we design automation in a way that makes data usable and enables future-ready digital business modelsâwith a clear focus on data, UX, and architecture.
Products & services
From Intelligent to Associative Automation
We support leading industrial companies in their digital transformation and pave the way for intelligent automation solutions â by implementing structured data models, modular architectures, and user-centered software. From the learnings of this collaboration, a clear perspective emerges for us: the future lies in ððððŒð°ð¶ð®ðð¶ðð² ððððŒðºð®ðð¶ðŒð» â automation that understands relationships, supports decision-making, and can grow with the complexity of modern systems. Our talk is aimed in particular at OEMs and integrators. We present selected case studies, put our insights into context, and explain what concrete first steps toward the future of automation can look like.
horstOS: KI-gestÃŒtztes Betriebssystem fÃŒr Industrieroboter
ðð»ððð¶ðð¶ðð² ððððŒðºð®ðð¶ðŒð» ð³ðŒð¿ ððµð² ð¡ð²ð ð ð¶ððð²ð¹ððð®ð»ð± fruitcore robotics pursues a clear vision: making industrial automation accessible to small and medium-sized enterprises. This takes more than robots aloneâit requires integrated system solutions that fit seamlessly into existing processes. With horstOS, an AI-powered operating system for configuring and operating industrial robots, we jointly reached a milestone on this mission and paved the way for fruitcoreâs transition from a traditional robotics manufacturer to a software-driven solution provider. ðð¿ðŒðº ðð®ð¿ð±ðð®ð¿ð² ð ð®ð»ðð³ð®ð°ððð¿ð²ð¿ ððŒ ðð¶ðŽð¶ðð®ð¹ ðð»ð®ð¯ð¹ð²ð¿ Small and medium-sized enterprises face multiple market challenges: development cycles must become shorter, flexibility must increase, and at the same time there is a shortage of skilled labor. Industrial robots can helpâbut they are often complex to implement and economically demanding. This is the space in which fruitcore robotics operates. Their central question: How can robots become smarter, more modular, and more intuitiveâwithout compromising industrial performance? Our shared answer: a strategic realignment with a strong focus on software, AI, and user-centric design.
Fabrik der Zukunft: Modulares Software-Ãkosystem fÃŒr smarte Werkzeugmaschinen
ððŒð»ðð¶ððð²ð»ð°ð ð®ð»ð± ððŒð»ð»ð²ð°ðð¶ðð¶ðð ð¶ð» ððµð² ð£ð¿ðŒð±ðð°ðð¶ðŒð» ð£ð¿ðŒð°ð²ðð Together with the EMAG Group and our partner Intuity, we developed a modular HMI software for machine tools. EMAG machines cover all relevant metalworking processes and, at the start of the project, relied on heterogeneous panels and data systems. By standardizing the data format, we created a unified user interface across different machine typesâclearly structured, consistent, and interconnected. ððŒðºðœð¹ð²ð ð¥ð²ðŸðð¶ð¿ð²ðºð²ð»ðð ð®ð»ð± ð ðŒð±ðð¹ð®ð¿ ðŠðððð²ðºð â ð¡ðŒ ð¢ð»ð²-ðŠð¶ðð²-ðð¶ðð-ðð¹ð¹ High functional depth, diverse machine types, and variable user journeys made the development highly complex. The software must cover a wide range of operating contextsâfrom machine operators to process engineersâand respond in real time to machine status, components, automation, and service cases. Added to this are variable screen sizes (stationary/mobile), touch interactions, and strict safety requirements in a production environment. Together, we developed a modular frontend system based on React. The goal was to establish a consistent, abstracted control layer across machine typesâforming the basis for consistent user interactions and interoperable data flows in line with Industry 4.0 principles. The widget-based architecture provides both overview and technical depth: from NC code editors and maintenance widgets to automated workpiece configuration.
Chirurgische QualitÀt mit KI bewerten und verbessern
ðð²ð®ð¿ð»ð¶ð»ðŽ ð³ð¿ðŒðº ðð®ðð®: ð§ðµð² ð£ð®ððµ ððŒ ð ð²ð®ððð¿ð®ð¯ð¹ð² ðŠðð¿ðŽð¶ð°ð®ð¹ ð€ðð®ð¹ð¶ðð The Surgical AI Hub Germany aims to make surgical quality data-driven and transparentâso that surgeons can use the insights gained in a targeted way for their own professional development. By applying AI-based analysis to surgical video recordings, the initiative is creating a platform that makes surgical procedures transparent and supports individual training as well as professional exchange among surgeons. ðð¿ðŒðº ð¥ð®ð ðð®ðð® ððŒ ð€ðð®ð¹ð¶ðð ð ð²ðð¿ð¶ð°ð The projectâs technical complexity lies in the sheer volume and heterogeneity of the data: gigabytes of video information must be analyzedâwhile strictly complying with data protection requirements. In addition to a technical demonstrator that maps the full functional pipeline from data capture to analysis, an interactive click dummy was developed and is used for extensive UX testing in clinical environments. Both components are already being presented to expert panels and at international conferencesâas tangible examples of a new generation of data-driven quality assurance in the operating room.
Teilautonomes Fahren fÃŒr E-RollstÃŒhle zur Kollisionsvermeidung
The goal of the project was to promote the independence of people with mobility impairments through a semi-autonomous electric wheelchair system. An innovative tech stack combining sensors, actuators, and middleware was intended to demonstrate new possibilitiesâfrom safe navigation in everyday life to intelligent interaction with the surrounding environment. At the same time, the project served as an exciting testbed for future mobility services in the fields of care, health, and smart assistance. The greatest technical challenge was achieving safe and precise real-time localization, particularly at low speeds and in unstructured, confined environments. The central task therefore lay not only in selecting precise sensors, but also in building a robust, economically viable hardware setup that functions reliably over the long term and is suitable for series production. In collaboration with Alber, we developed a modular simulation environment based on ROS 2 to efficiently and safely evaluate different sensor and communication architectures. A combination of two LiDAR sensors was used to enable robust, real-time environmental perception. With the help of SLAM algorithms, the environment was dynamically mapped and made navigable. For the implementation of the Simultaneous Localization and Mapping algorithms, the ROS 2 SlamToolbox was used. Based on the two LiDAR sensors, an environment map was created from which a costmap was generated: a two-dimensional representation that distinguishes drivable from non-drivable areas. This costmap forms the basis for the systemâs automatic route planningâthe algorithm calculates the most efficient and safest route to a previously defined target point. To control the system and ensure practical usability, we developed a mobile app using Flutter.