Four Flying Robots Learn Together скачать в хорошем качестве

Four Flying Robots Learn Together

In this video, we applied our Distributed Iterative Learning Control (ILC) approach to a team of four quadrotors. Four vehicles learn to synchronize their motion. A previous experiment with two quadrotors is found here:    • Distributed Iterative Learning Control for...   The goal of our work is to enable a team of robots to learn how to accurately track a desired trajectory while holding a given formation. We solve this problem in a distributed manner, where each vehicle has only access to the information of its neighbors and no central control unit is necessary. The desired trajectory is only available to one vehicle. We present a distributed iterative learning control (ILC) approach where the same task is repeated several times. Each vehicle learns from the experience of its own and its neighbors’ previous task repetitions and adapts its feedforward input to improve performance. **** For theoretic details, check the corresponding paper on arXiv: http://arxiv.org/pdf/1603.05933v1.pdf Work by Andreas Hock and Angela P. Schoellig at the Dynamic Systems Lab (http://www.dynsyslab.org), University of Toronto Institute for Aerospace Studies (UTIAS), Canada. This research was supported in part by NSERC grant RGPIN-2014-04634, the Connaught New Researcher Award and the Baden-Württemberg-STIPENDIUM. Music: Bitbasic - Please Mind the Dubstep Source: http://freemusicarchive.org/music/bit... ****