基于控制屏障的遥控操作与视觉-惯性SLAM的MAV安全导航
Control-Barrier-Aided Teleoperation with Visual-Inertial SLAM for Safe MAV Navigation in Complex Environments
AI总结：
本文提出了一种结合控制屏障函数与视觉-惯性SLAM的MAV安全导航系统，通过感知-动作闭环实现复杂环境中的安全遥控操作。
摘要：
本文考虑了一种由非专家遥控的微型飞行器（MAV）系统，并引入了一种感知安全过滤器，该过滤器结合了控制屏障函数（CBFs）与视觉-惯性同时定位与建图（VI-SLAM）和密集3D占用地图，以确保在复杂和无结构环境中安全导航。我们的系统仅依赖于机载IMU测量、立体红外图像和深度图像，并在认为输入不安全时自动纠正遥控输入。我们定义三维空间中的点为不安全的条件是：（i）被障碍物占据，或（ii）未被映射。在每个时间步，通过融合机载测量更新环境占用地图，构建一个CBF来参数化三维空间中的（不安全）区域。给定CBF和VI-SLAM模块的状态反馈，安全过滤器计算一个认证参考，该参考最好匹配遥控输入并满足由CBF编码的安全约束。与现有基于感知的安全控制框架不同，我们直接闭合感知-动作回路，并展示了安全控制与实时VI-SLAM结合的全部能力，而无需任何外部基础设施或环境的先验知识。我们通过仅使用机载传感和计算的实时MAV实验验证了感知安全过滤器的有效性，并表明即使在任意输入由遥控员发送的情况下，遥控MAV也能安全导航通过未知环境。
英文摘要：
In this paper, we consider a Micro Aerial Vehicle (MAV) system teleoperated by a non-expert and introduce a perceptive safety filter that leverages Control Barrier Functions (CBFs) in conjunction with Visual-Inertial Simultaneous Localization and Mapping (VI-SLAM) and dense 3D occupancy mapping to guarantee safe navigation in complex and unstructured environments. Our system relies solely on onboard IMU measurements, stereo infrared images, and depth images and autonomously corrects teleoperated inputs when they are deemed unsafe. We define a point in 3D space as unsafe if it satisfies either of two conditions: (i) it is occupied by an obstacle, or (ii) it remains unmapped. At each time step, an occupancy map of the environment is updated by the VI-SLAM by fusing the onboard measurements, and a CBF is constructed to parameterize the (un)safe region in the 3D space. Given the CBF and state feedback from the VI-SLAM module, a safety filter computes a certified reference that best matches the teleoperation input while satisfying the safety constraint encoded by the CBF. In contrast to existing perception-based safe control frameworks, we directly close the perception-action loop and demonstrate the full capability of safe control in combination with real-time VI-SLAM without any external infrastructure or prior knowledge of the environment. We verify the efficacy of the perceptive safety filter in real-time MAV experiments using exclusively onboard sensing and computation and show that the teleoperated MAV is able to safely navigate through unknown environments despite arbitrary inputs sent by the teleoperator.
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。
