Resilient Terrain Navigation with a 5 DOF Metal Detector Drone
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Author / Producer
Date
2023
Publication Type
Conference Paper
ETH Bibliography
yes
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Abstract
Micro aerial vehicles (MAVs) hold the potential for performing autonomous and contactless land surveys for the detection of landmines and explosive remnants of war (ERW). Metal detectors are the standard detection tool but must be operated close to and parallel to the terrain. A successful combination of MAVs with metal detectors has not been presented yet, as it requires advanced flight capabilities. To this end, we present an autonomous system to survey challenging undulated terrain using a metal detector mounted on a 5 degrees of freedom (DOF) MAV. Based on an online estimate of the terrain, our receding-horizon planner efficiently covers the area, aligning the detector to the surface while considering the kinematic and visibility constraints of the platform. As the survey requires resilient and accurate localization in diverse terrain, we also propose a factor graph-based online fusion of GNSS, IMU, and LiDAR measurements. We validate the robustness of the solution to individual sensor degeneracy by flying under the canopy of trees and over featureless fields. A simulated ablation study shows that the proposed planner reduces coverage duration and improves trajectory smoothness. Real-world flight experiments showcase autonomous mapping of buried metallic objects in undulated and obstructed terrain.
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Publication status
published
Editor
Book title
2023 IEEE International Conference on Robotics and Automation (ICRA)
Journal / series
Volume
Pages / Article No.
10652 - 10658
Publisher
IEEE
Event
40th IEEE International Conference on Robotics and Automation (ICRA 2023)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Organisational unit
03737 - Siegwart, Roland Y. / Siegwart, Roland Y.
02284 - NFS Digitale Fabrikation / NCCR Digital Fabrication
Notes
Funding
205604 - NCCR Digital Fabrication: Innovative Building Processes in Architecture (phase III) (SNF)
Related publications and datasets
Is new version of: 10.48550/arXiv.2212.07132