The detection and characterization of planets orbiting other stars than the Sun, i.e., so-called extrasolar planets, is one of the fastest growing and most vibrant research fields in modern astrophysics. In the last 25 years, more than 5400 extrasolar planets and planet candidates were revealed, but the vast majority of these objects was detected with indirect techniques, where the existence of the planet is inferred from periodic changes in the light coming from the central star. No photons from the planets themselves are detected. In this talk, however, I will focus on the direct detection of extrasolar planets. On the one hand I will describe the main challenges that have to be overcome in order to image planets around other stars. In addition to using the world’s largest telescopes and optimized cameras it was realized in last few years that by applying advanced image processing techniques significant sensitivity gains can be achieved. On the other hand I will demonstrate what can be learned if one is successful in “taking a picture” of an extrasolar planet. After all, there must be good scientific reasons and a strong motivation why the direct detection of extrasolar planets is one of the key science drivers for current and future projects on major ground- and space-based telescopes.
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems