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Multiple Drone Lidar Cooperation

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This paper focuses on mission planning and cooperative navigation algorithms for multiple drone systems aimed at LiDAR-based mapping. It aims at demonstrating how multi-UAV cooperation can be used to fulfill LiDAR data georeferencing accuracy requirements, as well as to improve data collection capabilities, e.g., increasing coverage per unit time and point cloud density. These goals are achieved by exploiting the CDGNSS/Vision paradigm and properly defining the formation geometry and the UAV trajectories.

From a paper by Flavia Causa, et al.

The paper provides analytical tools to estimate point density considering different types of scanning LIDAR and to define attitude/pointing requirements. These tools are then used to support centralized cooperation-aware mission planning aimed at complete coverage for different target geometries.

The validity of the proposed framework is demonstrated through numerical simulations considering a formation of three vehicles tasked with a powerline inspection mission. The results show that cooperative navigation allows for the reduction of angular and positioning estimation uncertainties, which results in a georeferencing error reduction of an order of magnitude and equal to 16.7 cm in the considered case.

Unmanned aerial vehicle (UAV)’s flexibility and adaptiveness to several environments have stimulated their usage in multiple application domains to execute tasks which required humans or manned vehicles in the past. Besides these applications, new missions are expected to be carried out by UAVs in the next few years, including urban transportation and delivery within the Advanced Air Mobility framework [1].

As a consequence, the UAV market is constantly growing and is expected to be worth hundreds of billions of
dollars at the end of this decade. Forty-five percent of the current UAV market [2] includes
infrastructure inspection and monitoring, and several scientific and industrial products
have been developed to make UAVs and their embarked payloads more and more effective in performing these missions [3]. Electro-optical sensors, like passive cameras or Light Detection and Ranging (LiDAR) instruments, are typically used as mapping payloads, i.e., to collect data suitable for creating a georeferenced 3D map of the environment, in several scenarios [4], including the inspection of powerlines [5], bridges [6], and ground terrain [7,8].

If LiDAR is used, the 3D map generation task requires an accurate UAV navigation
solution to be retrieved, as well as that the platform path is properly defined to solve the
complete coverage problem (CCP) of the area or object to inspect.

For the complete article on multiple drone lidar CLICK HERE.

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