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Autonomous navigation in unknown environments with obstacles remainschallenging for micro aerial vehicles (MAVs) due to their limited onboardcomputing and sensing resources. Although various collision avoidance methodshave been developed, it is still possible for drones to collide with unobservedobstacles due to unpredictable disturbances, sensor limitations, and controluncertainty. Instead of completely avoiding collisions, this article proposesAir Bumper, a collision detection and reaction framework, for fully autonomousflight in 3D environments to improve the safety of drones. Our framework onlyutilizes the onboard inertial measurement unit (IMU) to detect and estimatecollisions. We further design a collision recovery control for rapid recoveryand collision-aware mapping to integrate collision information into generalLiDAR-based sensing and planning frameworks. Our simulation and experimentalresults show that the quadrotor can rapidly detect, estimate, and recover fromcollisions with obstacles in 3D space and continue the flight smoothly with thehelp of the collision-aware map. Our Air Bumper will be released as open-sourcesoftware on GitHub.

Air Bumper: A Collision Detection and Reaction Framework for Autonomous MAV Navigation