笔者评：UAV自动导航技术在室外主要利用GPS定位信息，但在室内自主导航就和地面机器人一样，需要采用类似SLAM等的技术进行自主定位和导航，点云获取与处理则在整个流程中起到非常重要的作用。Warwick Mobile Robotics 近期发布了一项博士的研究课题，是开发基于SLAM的室内无人机UAV自动导航原型，其中为了精确定位， 选择Xsens MTi sensor作为UAV的位姿传感器。
Warwick Mobile Robotics is a collection of projects under development at the University of Warwick in the field of mobile robotics. One of these projects involves the development of an indoor aerial inspection vehicle. This PhD project is sponsored by Sellafield Ltd, and aims to build a prototype UAV to fly inside structurally unsafe, hazardous or radioactive buildings for the purpose of inspecting and identifying hazards.
There are many industrial sites and buildings that have features that are difficult to reach or hazardous for humans to enter but nevertheless require inspection from time to time for routine or emergency reasons. Much progress has been made in recent years in the application of unmanned miniature aircraft, and radio controlled electric helicopters can now achieve flight times of up to to 15 minutes with lithium batteries. Manually flying a remote controlled helicopter in a confined area with obstacles is difficult and requires very good situational awareness. In many circumstances the UAV may be out of sight of the operator who will have to rely solely on on-board cameras, possibly in low light conditions, significantly reducing situational awareness and increasing the risk of collisions.
This project was conceived to develop a UAV that would be as autonomous as possible with current technologies, only requiring the operator to provide it with its destination coordinates. The UAV then pilots itself to the destination avoiding any obstacles en route. Stefan Winkvist, Project leader of the UAV team adds: “It was discovered early on in the project that an accurate yet light weight orientation sensor was a key component for the project’s success. After researching many different IMU systems an Xsens MTi sensor was chosen, mainly due to its compact size, robustness, ease of use and overall accuracy when compared with similarly priced sensors.”