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MULTI-SENSOR FUSION FOR ROBUST AUTONOMOUS FLIGHT IN INDOOR AND OUTDOOR ENVIRONMENTS WITH A ROTORCRAFT MICRO-AERIAL VEHICLE (MAV)
MULTI-SENSOR FUSION FOR ROBUST AUTONOMOUS FLIGHT IN INDOOR AND OUTDOOR ENVIRONMENTS WITH A ROTORCRAFT MICRO-AERIAL VEHICLE (MAV)
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机译：带有涡轮微动车辆（MAV）的室内和室外环境中强健自主飞行的多传感器融合
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摘要
The subject matter described hereinincludes a modular and extensible approach to integratenoisy measurements from multiple heterogeneous sensorsthat yield either absolute or relative observations atdifferent and varying time intervals, and to provide smooth andglobally consistent estimates of position in real time forautonomous flight. We describe the development of thealgorithms and software architecture for a new 1.9 kg MAVplatform equipped with an IMU, laser scanner, stereocameras, pressure altimeter, magnetometer, and a GPSreceiver, in which the state estimation and control are performedonboard on an Intel NUC 3rd generation i3 processor. Weillustrate the robustness of our framework in large-scale,indoor-outdoor autonomous aerial navigation experimentsinvolving traversals of over 440 meters at average speedsof 1.5 m/s with winds around 10 mph while entering andexiting buildings.
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机译：本文所述的主题包括模块化和可扩展的方法来集成来自多个异构传感器的噪声测量产生绝对或相对观测值不同和变化的时间间隔，并提供流畅的全球实时一致的位置估计自主飞行。我们描述了新型1.9千克MAV的算法和软件架构平台，配有IMU，激光扫描仪，立体声摄像头，压力高度计，磁力计和GPS接收器，其中执行状态估计和控制搭载在Intel NUC第三代i3处理器上。我们说明了我们框架的大规模鲁棒性，室内外自主空中航行实验涉及以平均速度穿越440米以上进入时风速为1.5 m / s，风速约为10 mph退出建筑物。
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