Toward a Fully Autonomous UAV Research Platform for Indoor and Outdoor Urban Search and Rescue
Toward a Fully Autonomous UAV Research Platform for Indoor and Outdoor Urban Search and Rescue
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DOI：
10.1109/mra.2012.2206473
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发表时间：
2012-09-01
影响因子：
5.7
通讯作者：
Burschka, Darius
中科院分区：
文献类型：
--
作者：
Tomic, Teodor;Schmid, Korbinian;Burschka, Darius
城市搜索和救援任务对机器人系统提出了特殊要求。小型航空系统为人类特遣部队提供了必要的支持，以进行情况评估和监视。由于用于导航和通信的外部基础设施通常不可用，机器人系统必须能够自主操作。小型航空系统的有效载荷有限，给系统设计带来了很大的挑战。必须在飞行性能、传感器和计算资源之间找到最佳折衷。无法保证与外部计算机的通信;因此，所有处理和决策都必须在机上完成。在这篇文章中，我们提出了一个无人驾驶飞机系统设计满足这些要求。我们系统的组件被组织成组，以封装它们的功能和接口。我们使用激光和立体视觉里程计来实现室内和室外的无缝导航。在扩展卡尔曼滤波器中将里程计与惯性测量单元融合。导航由一个模块支持，该模块识别环境中的已知对象。采用分布式计算方法来解决所用算法的计算要求。该系统的能力进行了验证，在飞行实验中，使用四旋翼。
Urban search and rescue missions raise special requirements on robotic systems. Small aerial systems provide essential support to human task forces in situation assessment and surveillance. As external infrastructure for navigation and communication is usually not available, robotic systems must be able to operate autonomously. A limited payload of small aerial systems poses a great challenge to the system design. The optimal tradeoff between flight performance, sensors, and computing resources has to be found. Communication to external computers cannot be guaranteed; therefore, all processing and decision making has to be done on board. In this article, we present an unmanned aircraft system design fulfilling these requirements. The components of our system are structured into groups to encapsulate their functionality and interfaces. We use both laser and stereo vision odometry to enable seamless indoor and outdoor navigation. The odometry is fused with an inertial measurement unit in an extended Kalman filter. Navigation is supported by a module that recognizes known objects in the environment. A distributed computation approach is adopted to address the computational requirements of the used algorithms. The capabilities of the system are validated in flight experiments, using a quadrotor.