Air Bumper：一种用于自主微型飞行器导航的碰撞检测与反应框架
Air Bumper: A Collision Detection and Reaction Framework for Autonomous MAV Navigation
AI总结：
本文提出 Air Bumper 框架，仅利用机载 IMU 实现三维环境中 MAV 的碰撞检测、估计与快速恢复控制，并通过碰撞感知建图将碰撞信息融入 LiDAR 感知与规划，提升无人机飞行安全性。
摘要：
由于机载计算和传感资源有限，微型飞行器（MAV）在未知障碍物环境中的自主导航仍然具有挑战性。尽管已经开发了各种避碰方法，但由于不可预测的扰动、传感器限制和控制不确定性，无人机仍有可能与未观测到的障碍物发生碰撞。本文没有完全避免碰撞，而是提出了 Air Bumper，一种用于三维环境中全自主飞行的碰撞检测与反应框架，以提高无人机的安全性。我们的框架仅利用机载惯性测量单元（IMU）来检测和估计碰撞。我们进一步设计了碰撞恢复控制以实现快速恢复，并设计了碰撞感知建图，将碰撞信息集成到基于 LiDAR 的通用感知和规划框架中。我们的仿真和实验结果表明，四旋翼无人机能够快速检测、估计并从三维空间中的障碍物碰撞中恢复，并借助碰撞感知地图平稳地继续飞行。我们的 Air Bumper 将作为开源软件在 GitHub 上发布。
英文摘要：
Autonomous navigation in unknown environments with obstacles remains challenging for micro aerial vehicles (MAVs) due to their limited onboard computing and sensing resources. Although various collision avoidance methods have been developed, it is still possible for drones to collide with unobserved obstacles due to unpredictable disturbances, sensor limitations, and control uncertainty. Instead of completely avoiding collisions, this article proposes Air Bumper, a collision detection and reaction framework, for fully autonomous flight in 3D environments to improve the safety of drones. Our framework only utilizes the onboard inertial measurement unit (IMU) to detect and estimate collisions. We further design a collision recovery control for rapid recovery and collision-aware mapping to integrate collision information into general LiDAR-based sensing and planning frameworks. Our simulation and experimental results show that the quadrotor can rapidly detect, estimate, and recover from collisions with obstacles in 3D space and continue the flight smoothly with the help of the collision-aware map. Our Air Bumper will be released as open-source software on GitHub.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
