CoRL 2020, Spotlight Talk 250: Flightmare: A Flexible Quadrotor Simulator

CoRL 2020

CoRL 2020, Spotlight Talk 250: Flightmare: A Flexible Quadrotor Simulator

Dec 16, 2020
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**Flightmare: A Flexible Quadrotor Simulator** Yunlong Song (ETH / University of Zurich)*; Selim Naji (ETH / Univ. of Zurich); Elia Kaufmann (ETH / University of Zurich); Antonio Loquercio (ETH / University of Zurich); Davide Scaramuzza (University of Zurich & ETH Zurich, Switzerland) Publication: http://corlconf.github.io/paper_250/ **Abstract** State-of-the-art quadrotor simulators have a rigid and highly-specialized structure: either are they really fast, physically accurate, or photo-realistic. In this work, we propose a paradigm shift in the development of simulators: moving the trade-off between accuracy and speed from the developers to the end-users. We use this idea to develop a flexible quadrotor simulator: Flightmare. In this work, we propose a novel quadrotor simulator: Flightmare. Flightmare is composed of two main components: a configurable rendering engine built on Unity and a flexible physics engine for dynamics simulation. Those two components are totally decoupled and can run independently of each other. This makes our simulator extremely fast: rendering achieves speeds of up to 230 Hz, while physics simulation of up to 200,000 Hz on a laptop. In addition, Flightmare comes with several desirable features: (i) a large multi-modal sensor suite, including an interface to extract the 3D point-cloud of the scene; (ii) an API for reinforcement learning which can simulate hundreds of quadrotors in parallel; and (iii) integration with a virtual-reality headset for interaction with the simulated environment. We demonstrate the flexibility of Flightmare by using it for two different robotic tasks: quadrotor control using deep reinforcement learning and collision-free path planning in a complex 3D environment.

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