Benjamin Schellenberg

Mr. Benjamin Schellenberg

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Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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24 July 2019 in Journal of Field Robotics
Verified
Journal Article
Open access
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BSBenjamin Schellenberg
Benjamin Schellenberg
TRTom Richardson
Tom Richardson
MWMatt Watson
Matt Watson
CGColin Greatwood
Colin Greatwood
RCRobert Clarke
Robert Clarke
GCGustavo Chigna
Gustavo Chigna
This paper describes a series of proof‐of‐concept Beyond Visual Line Of Sight unmanned aerial vehicle flights which reached a range of up to 9 km and an altitude of 4,410 m Above Mean Sea Level over Volcán de Fuego in Guatemala, interacting with the volcanic plume on multiple occasions across a range of different conditions. Volcán de Fuego is an active volcano which emits gas and ash regularly, causing disruption to airlines operating from the international airport 50 km away and impacting the lives of the local population. Collection of data from within the plume develops scientists’ understanding of the composition of the volcano's output and is of use to scientists, aviation, and hazard management groups alike. This paper presents preliminary results of multiple plume interceptions with multiple aircraft, carrying a variety of sensors. A plume‐detection metric is introduced, which uses a combination of flight data and atmospheric sensor data to identify flight through a volcanic plume. Future work will develop the automation of plume tracking such that reliable scientific data sets can be gathered in a robust manner.

21 September 2019 in Sensors
Verified
Journal Article
Open access
PDF file
BSBenjamin Schellenberg
Benjamin Schellenberg
TRThomas Richardson
Thomas Richardson
ARArthur Richards
Arthur Richards
RCRobert Clarke
Robert Clarke
MWMatthew Watson
Matthew Watson
A team from the University of Bristol have developed a method of operating fixed wing Unmanned Aerial Vehicles (UAVs) at long-range and high-altitude over Volcán de Fuego in Guatemala for the purposes of volcanic monitoring and ash-sampling. Conventionally, the mission plans must be carefully designed prior to flight, to cope with altitude gains in excess of 3000 m, reaching 9 km from the ground control station and 4500 m above mean sea level. This means the climb route cannot be modified mid-flight. At these scales, atmospheric conditions change over the course of a flight and so a real-time trajectory planner (RTTP) is desirable, calculating a route on-board the aircraft. This paper presents an RTTP based around a genetic algorithm optimisation running on a Raspberry Pi 3 B+, the first of its kind to be flown on-board a UAV. Four flights are presented, each having calculated a new and valid trajectory on-board, from the ground control station to the summit region of Volcań de Fuego. The RTTP flights are shown to have approximately equivalent efficiency characteristics to conventionally planned missions. This technology is promising for the future of long-range UAV operations and further development is likely to see significant energy and efficiency savings.