Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away.
—Antoine de Saint-Exupéry
Recent developments within the field of autonomous systems and advanced machine learning and AI applications have led to new needs in production processes, over-the-air software updates and monitoring, and functional verification. Pionate offers a middleware for such advanced and modern systems that efficiently meet these new demands.
From long experience within the field of autonomous vehicles and robotics, Pionate have created a middleware from the ground up that greatly outperforms other similar software solutions such as the Robotic operating system (ROS), especially when it comes to reduced complexity, production-friendliness, and modularity.
The Pionate middleware is designed in a modular and minimalistic way, to allow for outstanding integration possibilities and reduced overall system complexity. The modularity allows systems to be tailored for any need, without the risk of adding unused software leading to increased complexity and larger attack surfaces.
The recent trends show drastically increased software sizes in modern embedded systems.
The reason is often fundamentally bad software architecture designs, which might lead to:
Complexity is a cost driver at all levels of production!
The size of the Pionate middleware is just a fraction of other alternatives!
Based on modern system design principles, Pionate develops safe and efficient real-time systems for autonomous vehicles and similar demanding and safety-critical applications. The very compact system has been optimized for large-scale data flows and fast decision making. This improves safety, reduces the risk for cyber attacks, lowers energy consumption, results in lower demands for advanced hardware while enabling efficient high-volume production, updates, and live monitoring.
Pionate has turned recent research findings in designing microservice-based safety-critical systems, combined with modern software engineering principles, into a prototype ready for tests in realistic settings and for demonstrations.