Abstract

Unmanned aerial vehicle (UAV) is a flying device that is integrated with appropriate hardware and software, besides it is also a device to collect and process data to meet the needs and purposes of users. Currently, most drones use GPS technology to determine the flight path, and other sensors on it are used to determine distance, avoid collisions. However, with small, narrow spaces, dangerous environments that humans cannot go into that space, GPS not working, small drones with small hardware devices placed on it to map themselves and navigation would be a suitable solution. In this paper, a method to build a high-performance reconfigurable computing environment model to map drone as well as UAV flying in 3D space is proposed. Mapping based on Boolean formulas with reconfigurable structure and adjustable automatons will generate high-precision maps for efficient robot navigation.

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