Current Projects
Pushing the Boundary of Autonomous Systems
Distributed Flight Array
We are on the threshold of being able to place sensors and actuators everywhere. This has been precipitated in part by rapid advances in manufacturing technology, which will soon allow us to embed actuators and sensors on almost any physical device – from the nano-scale to the macro-scale – at an economically viable cost. Fortunately, computing and communications technology have been keeping pace with these advances, and all the ingredients are present for major breakthroughs in how we control and interface with our environment.
Serious challenges, however, must be overcome.
Balancing Cube
One of the most significant of these is the present difficulty in making appropriate decisions based on distributed information. It is well known that two simple dynamic systems can exhibit comparatively complex behavior when interconnected; the present challenge is to effectively design and control systems with many interconnected components.
And yet, with the appropriate use of filtering, estimation and prediction, the interface between these interconnected components and the high-level algorithms that control them can be greatly simplified.
In addition, Optimal Control can be used to create motion primitives, Adaptive Control and Machine Learning can be used to improve system performance over time and to cope with changing conditions, Mixed Integer-Linear Programming can be used to design cooperative strategies, and Distributed Estimation can be used to build models of the environment from multiple, error-prone sources.
In short, we are now capable of designing and controlling autonomous systems that learn from experience and improve their performance over time.
Flying Machine Arena
Part of our research at the IDSC labs at ETH Zurich is to develop tools for designing and controlling complex systems such as these. We motivate our research by building state-of-the-art test-beds, such as a multi-vehicle Flying Machine Arena, machines that balance and juggle, and self-organizing mobile structures. Each of these projects push the boundary of what can be achieved with feedback control in its broadest sense.
"The Blind Juggler"
The nature of the underlying architecture of these systems is crucial to their success. To be effective, they must be modular, easy to adapt, and allow a large number of individuals to concurrently develop them. This is why, from a pedagogical perspective, we have adopted a multi-disciplinary team-based approach to many of our projects: individuals learn how to create modular subsystems that can easily interface with the subsystems created by other members of their team, and in the process acquire a solid understanding of feedback, dynamics and control.
This kind of ‘building block’ approach – where each self-contained subsystem can be easily put to use by non-experts – is crucial to effective systems engineering, where individuals across many fields must collaborate, and where requirement-driven design, manufacturability, maintainability and simulation are key.
Raffaello D’Andrea
Self-Organizing Structure
top
