Agilicious: Open-Source and Open-Hardware Agile Quadrotor for Vision-Based Flight
Agile flight done right!
Agilicious is a co-designed hardware and software framework tailored to autonomous, agile quadrotor flight, which has been developed and used since 2016 at the Robotics and Perception Group (RPG) of the University of Zurich. Agilicious is described in this Science Robotics 2022 paper. It is completely open-source and open-hardware and supports both model-based and neural-network-based controllers. Also, it provides high thrust-to-weight and torque-to-inertia ratios for agility, onboard vision sensors, GPU-accelerated compute hardware for real-time perception and neural-network inference, a real-time flight controller, and a versatile software stack. In contrast to existing frameworks, Agilicious offers a unique combination of flexible software and high-performance hardware. Agilicious has been used in over 30 scientific papers at our lab, including trajectory tracking for drone racing scenarios at up to 5g and 70km/h (SciRob21_Foehn, Video), vision-based acrobatic flight (RSS20 Kaufmann, Video), obstacle avoidance in both structured and unstructured environments using solely onboard perception (SciRob21_Loquercio, Video), and hardware-in-the-loop simulation in virtual-reality environments. Thanks to its versatility, we believe that Agilicious supports the next generation of scientific and industrial quadrotor research. Agilicious allows to seamlessly develop, test, reproduce and benchmark control algorithms such as Non-linear Model Predictive Control (MPC), differential-flatness-based control (DFBC) and INDI (Incremental Non-linear Dynamic Inversion) (TRO 2022, Sun, Video). Agilicious also includes our state-of-the-art, high-fidelity simulator, which uses Blade Element Momentum (BEM) theory for the propeller model and provides accurate estimates of the quadcopter’s aerodynamic characteristics across the flight envelope (RSS 2021, Bauersfeld, Video).