TY - JOUR
T1 - Autonomous UAS-based Water Fluorescence Mapping and Targeted Sampling
AU - Sanim, Kazi Ragib Ishraq
AU - English, Caitlyn
AU - Kitzhaber, Zechariah B.
AU - Kalaitzakis, Michail
AU - Vitzilaios, Nikolaos
AU - Myrick, Michael L.
AU - Hodgson, Michael E.
AU - Richardson, Tammi L.
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Nature B.V.
PY - 2023/6
Y1 - 2023/6
N2 - Uncrewed Aircraft Systems (UAS) are increasingly used in time-consuming and effort-heavy scientific exploration applications. One such application is the inspection of the physical, chemical, and biological properties of water in aquatic ecosystems. This paper presents a novel autonomous UAS capable of sensing water properties and collecting up to three 250 mL water samples from multiple sampling locations. The system features a customized UAS with an in-house built fluorescence sensor and pumping mechanism. The system does in situ fluorescence measurements to map the gradient of fluorescent content across the body of water and determine the best sampling spot for targeted sampling. To ensure safe near-water operation, multiple sensor fusion with an Extended Kalman Filter has been implemented for accurate altitude estimation within 1.5 m from the water surface. To validate the performance of the system, we present experimental results from deployment in two different water ecosystems, namely the Congaree River, SC and Lake Wateree, SC.
AB - Uncrewed Aircraft Systems (UAS) are increasingly used in time-consuming and effort-heavy scientific exploration applications. One such application is the inspection of the physical, chemical, and biological properties of water in aquatic ecosystems. This paper presents a novel autonomous UAS capable of sensing water properties and collecting up to three 250 mL water samples from multiple sampling locations. The system features a customized UAS with an in-house built fluorescence sensor and pumping mechanism. The system does in situ fluorescence measurements to map the gradient of fluorescent content across the body of water and determine the best sampling spot for targeted sampling. To ensure safe near-water operation, multiple sensor fusion with an Extended Kalman Filter has been implemented for accurate altitude estimation within 1.5 m from the water surface. To validate the performance of the system, we present experimental results from deployment in two different water ecosystems, namely the Congaree River, SC and Lake Wateree, SC.
KW - Autonomous navigation
KW - Extended kalman filter
KW - Remote sensing
KW - Sensor fusion
KW - Uncrewed aircraft system
KW - Water sampling
UR - http://www.scopus.com/inward/record.url?scp=85162017474&partnerID=8YFLogxK
U2 - 10.1007/s10846-023-01880-9
DO - 10.1007/s10846-023-01880-9
M3 - Article
AN - SCOPUS:85162017474
SN - 0921-0296
VL - 108
JO - Journal of Intelligent and Robotic Systems: Theory and Applications
JF - Journal of Intelligent and Robotic Systems: Theory and Applications
IS - 2
M1 - 25
ER -