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Agilicious is an open-source hardware and software framework for agile quadrotor flight. This versatile platform accelerates research in autonomous robotics by integrating high-performance hardware with flexible software for advanced control and perception.

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Area of Science:

  • Robotics
  • Autonomous Systems
  • Control Theory

Background:

  • Autonomous, agile quadrotor flight presents significant challenges in perception, planning, learning, and control.
  • Existing research platforms often lack the versatility and standardization needed to accelerate progress.

Purpose of the Study:

  • To introduce Agilicious, a novel, open-source, codesigned hardware and software framework specifically for autonomous, agile quadrotor flight.
  • To provide a standardized platform that enables researchers to focus on core challenges in quadrotor robotics.

Main Methods:

  • Developed a codesigned hardware and software framework featuring high thrust-to-weight and torque-to-inertia ratios.
  • Integrated onboard vision sensors, GPU-accelerated compute hardware, and a real-time flight controller.
  • Supported both model-based and neural network-based controllers within a versatile software stack.

Main Results:

  • Demonstrated Agilicious on various agile tasks, including trajectory tracking at high speeds (70 km/h) and accelerations (up to 5g).
  • Showcased vision-based acrobatic flight and obstacle avoidance using only onboard perception in diverse environments.
  • Validated its utility for hardware-in-the-loop simulation in virtual reality.

Conclusions:

  • Agilicious offers a unique combination of high-performance hardware and flexible software, accelerating research in autonomous quadrotor flight.
  • The framework's versatility supports the next generation of scientific and industrial quadrotor applications.