Accurate 3D Localization for MAV Swarms by UWB and IMU Fusion

July 28, 2018 · Entered Twilight · 🏛 2018 IEEE 14th International Conference on Control and Automation (ICCA)

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Repo contents: LICENSE, README.md, common_msgs, images, slam_pp, time_domain, uwb_calibration

Authors Jiaxin Li, Yingcai Bi, Kun Li, Kangli Wang, Feng Lin, Ben M. Chen arXiv ID 1807.10913 Category cs.RO: Robotics Citations 92 Venue 2018 IEEE 14th International Conference on Control and Automation (ICCA) Repository https://github.com/lijx10/uwb-localization ⭐ 411 Last Checked 3 months ago

Abstract

Driven by applications like Micro Aerial Vehicles (MAVs), driver-less cars, etc, localization solution has become an active research topic in the past decade. In recent years, Ultra Wideband (UWB) emerged as a promising technology because of its impressive performance in both indoor and outdoor positioning. But algorithms relying only on UWB sensor usually result in high latency and low bandwidth, which is undesirable in some situations such as controlling a MAV. To alleviate this problem, an Extended Kalman Filter (EKF) based algorithm is proposed to fuse the Inertial Measurement Unit (IMU) and UWB, which achieved 80Hz 3D localization with significantly improved accuracy and almost no delay. To verify the effectiveness and reliability of the proposed approach, a swarm of 6 MAVs is set up to perform a light show in an indoor exhibition hall. Video and source codes are available at https://github.com/lijx10/uwb-localization