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首页> 外文会议>IEEE International Conference on Robotics and Automation >The Tiercel: A novel autonomous micro aerial vehicle that can map the environment by flying into obstacles
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The Tiercel: A novel autonomous micro aerial vehicle that can map the environment by flying into obstacles

机译：Tiercel：一种新型的自动微型飞行器，可以通过飞入障碍物来绘制环境图

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Autonomous flight through unknown environments in the presence of obstacles is a challenging problem for micro aerial vehicles (MAVs). A majority of the current state-of-art research assumes obstacles as opaque objects that can be easily sensed by optical sensors such as cameras or LiDARs. However in indoor environments with glass walls and windows, or scenarios with smoke and dust, robots (even birds) have a difficult time navigating through the unknown space.In this paper, we present the design of a new class of micro aerial vehicles that achieves autonomous navigation and are robust to collisions. In particular, we present the Tiercel MAV: a small, agile, light weight and collision-resilient robot powered by a cellphone grade CPU. Our design exploits contact to infer the presence of transparent or reflective obstacles like glass walls, integrating touch with visual perception for SLAM. The Tiercel is able to localize using visual-inertial odometry (VIO) running on board the robot with a single downward facing fisheye camera and an IMU. We show how our collision detector design and experimental set up enable us to characterize the impact of collisions on VIO. We further develop a planning strategy to enable the Tiercel to fly autonomously in an unknown space, sustaining collisions and creating a 2D map of the environment. Finally we demonstrate a swarm of three autonomous Tiercel robots safely navigating and colliding through an obstacle field to reach their objectives.
机译：对于有障碍物的微型飞机而言，在未知环境中自动飞行是一个具有挑战性的问题。当前的大多数最新研究都将障碍物视为不透明物体，可以通过诸如相机或LiDARs之类的光学传感器轻松感知。但是，在玻璃墙和窗户的室内环境中，或者在有烟尘的场景中，机器人（甚至是鸟类）在未知空间中导航比较困难。自主导航并且对碰撞具有鲁棒性。特别是，我们介绍了Tiercel MAV：这是一款小型，敏捷，重量轻且具有防碰撞能力的机器人，由手机级CPU驱动。我们的设计利用接触来推断透明或反射性障碍物（例如玻璃墙）的存在，从而将触摸与SLAM的视觉感知整合在一起。 Tiercel能够使用在机器人上运行的视觉惯性里程计（VIO）进行定位，并带有单个向下的鱼眼镜头和IMU。我们展示了碰撞检测器的设计和实验设置如何使我们能够表征碰撞对VIO的影响。我们进一步制定了一项计划策略，以使Tiercel能够在未知空间中自主飞行，维持碰撞并创建环境的2D地图。最后，我们演示了由三个自主的Tiercel机器人组成的群体，这些机器人可以安全地在障碍场中导航和碰撞以达到其目标。

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