Mini Mapper: Cost-Effective Indoor Mapping and Navigation using Nano Drone

Abstract

Drones or unmanned aerial vehicles (UAVs) are utilized in indoor environments such as warehouses for monitoring, inventory management, etc. Although current indoor mapping technologies such as LiDAR and camera-based systems are effective, they require significant financial investment and computational resources. We address this challenge with the help of a solution based on nano drones equipped with basic distance sensors that efficiently map indoor spaces. Our unique approach uses two-dimensional distance measurements — similar to a single-point distance sensor rather than a 3D LiDAR scanner. Further, a navigation algorithm is developed to work with these simple sensors, accounting for their limited field of view. The system includes an innovative feature where a mapper drone maps the environment and generates viable paths, which other robots or drones can follow to explore the space efficiently. The algorithm and navigation setup were first tested in a simulation environment using Gazebo Sim where the follower drone traversed the mapper drone’s path with 93.05% accuracy. Finally, the algorithm was tested on a nanodrone(Crazyflie), which successfully avoided obstacles and produced the environmental map.