Build Your Own Visual-Inertial Drone: A Cost-Effective and Open-Source Autonomous Drone

Abstract

This paper describes an approach to building a cost-effective and research grade visualinertial odometry aided vertical taking-off and landing (VTOL) platform. We utilize an off-the-shelf visual-inertial sensor, an onboard computer, and a quadrotor platform that are factory-calibrated and mass-produced, thereby sharing similar hardware and sensor specifications (e.g., mass, dimensions, intrinsic and extrinsic of camera-IMU systems, and signal-to-noise ratio). We then perform system calibration and identification enabling the use of our visual-inertial odometry, multi-sensor fusion, and model predictive control frameworks with the off-the-shelf products. This approach partially circumvents the tedious parameter tuning procedures required to build a full system. The complete system is evaluated extensively both indoors using a motion capture system and outdoors using a laser tracker while performing hover and step responses, and trajectory following tasks in the presence of external wind disturbances. We achieve root-mean-square (RMS) pose errors of 0.036 m with respect to reference hover trajectories. We also conduct relatively long distance (≈180 m) experiments on a farm site, demonstrating 0.82% drift error of the total flight distance. This paper conveys the insights we acquired about the platform and sensor module and offers open-source code with tutorial documentation to the community.

UAV/UGV Autonomous Cooperation: UAV assists UGV to climb a cliff by attaching a tether

“…The navigation of the UAV runs on ROS. For the localization and position control, we followed the similar framework as [20]. The UAV uses Visual Inertial Odometry (VIO) to estimate the relative position and orientation from the reference frame.…”

VI-RPE: Visual-Inertial Relative Pose Estimation for Aerial Vehicles

“…The blue blocks are hardware. The green blocks are part of the open-drone stack [6]. We are using the non-linear MPC controller [15].…”

“…Our open-source system employs the open-source autonomous drone framework [6], rendering this work fully reproducible onboard a wide range of UAV platforms.…”

“…Aiming to overcome this, the framework in this paper, does not couple the pose estimation tightly to any controller. The proposed system is developed using the open-source drone stack [6], with the controller outside the loop. The controller available in this stack can perform model-based prediction of the UAV's pose in the near future.…”

Translating Aerial Images Into Street-Map-Like Representations for Visual Self-Localization of Uavs

“…Visual Odometry has been shown to alleviate the problem of short term GPS outages and can maintain a precise position estimation over a few hundred meters flight path (Sa et al, 2018) but is, similar to INS, also prone to drift over time.…”