Design and Characterization of a Multi-Domain Unmanned Vehicle Operating in Aerial, Terrestrial, and Underwater Environments

Dario Canelon, Sam Westlake, Youbing Wang, Nikolaos Papanikolopoulos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we demonstrate and validate the flight characteristics of a multi-domain unmanned platform capable of locomotion in the air, water, and land domains. The OmnibotV2 uses four flight motors in a quad-copter configuration for flight, a dual screwdrive system for land and water locomotion, and optionally features a buoyancy control unit for water operations. Experiments were performed to measure how maximum battery voltage, temperature, and motors of different torque-speed characteristics affect the performance of the platform in flight. Screwdrive locomotion similarly also evaluated on land, underwater, and on the water's surface. The transition between the water's surface and the air was validated as was the use of the flight propulsion for moving around in and under the water. A streaming camera unit as well as other sensors were integrated and validated for future applications in environmental monitoring.

Original languageEnglish (US)
Title of host publication2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1466-1471
Number of pages6
ISBN (Electronic)9780738131153
DOIs
StatePublished - Jun 15 2021
Event2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021 - Athens, Greece
Duration: Jun 15 2021Jun 18 2021

Publication series

Name2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021

Conference

Conference2021 International Conference on Unmanned Aircraft Systems, ICUAS 2021
Country/TerritoryGreece
CityAthens
Period6/15/216/18/21

Bibliographical note

Funding Information:
VI. ACKNOWLEDGEMENTS This material is based upon work partially supported by the Corn Growers Association of MN, the Minnesota Robotics Institute (MnRI), Honeywell, and the National Science Foundation through grants #CNS-1432957, #CNS-1544887, #CNS-1531330, and #CNS-1939033. USDA/NIFA has also supported this work through grant 2020-67021-30755.

Publisher Copyright:
© 2021 IEEE.

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