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Precise aggressive aerial maneuvers with sensorimotor policies.

Tianyue Wu1, Guangtong Xu2, Zihan Wang2

  • 1Institute of Cyber-Systems and Control, College of Control Science and Engineering, Zhejiang University, Hangzhou, China.

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Summary
This summary is machine-generated.

This study introduces sensorimotor policies for drones to perform aggressive maneuvers through narrow gaps. This enables drones to navigate challenging environments with enhanced precision and repeatability.

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Control Systems

Background:

  • Aggressive maneuvers are crucial for drones to navigate complex environments, but are limited by current sensor and control capabilities.
  • Traversing narrow gaps requires precise control and leveraging drone dynamics, posing a significant challenge for quadrotors.

Purpose of the Study:

  • To develop sensorimotor policies for quadrotors to perform aggressive maneuvers through narrow gaps using onboard sensors.
  • To enable drones to navigate complex environments by directly mapping sensory input to low-level control commands.

Main Methods:

  • Developed sensorimotor policies trained with reinforcement learning (RL) and end-to-end policy distillation in simulation.
  • Utilized a model-based planner for trajectory initialization to overcome RL exploration challenges.
  • Implemented careful sim-to-real transfer for robust real-world performance.

Main Results:

  • Successfully controlled a quadrotor through narrow gaps with 5cm clearance and 90° tilt, without prior knowledge of gap parameters.
  • Demonstrated reactive control for traversing moving gaps without specific training.
  • Validated the policy on diverse, challenging gap configurations, showcasing flexibility and repeatability.

Conclusions:

  • The developed sensorimotor policies enable precise and repeatable aggressive maneuvers for quadrotors in narrow gaps.
  • The approach offers a flexible and effective method for drone navigation in previously inaccessible environments.
  • This work advances drone capabilities for complex, real-world applications.