Adaptive and Nonadaptive Training Technology for Small Unmanned Aerial System Employment

Durlach, Paula J.; Dargue, Brandt; Goldberg, Stephen

doi:10.21236/ada557064

Cited by 2 publications

(4 citation statements)

References 9 publications

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“…This allowed for a collective exercise with a UXV and multiple friendly, hostile, and civilian entities, which provided the commander a mission context in which to employ the UXV. The initial findings support the potential for effective training using the UXV while on a mission [4], and after some further development on the platforms, would allow more complete exploration of team coordination issues and the training which would address them. Additional questions are now also being explored surrounding the factors involved in effective human-UXV teamwork.…”

Section: Automated Feedback Systemmentioning

confidence: 58%

“…Limitations in C2Node and SimOCU have largely been related to integration with other simulation systems. Integrating Research Network Inc.'s GDIS2 military training simulation (described in [4]) presented a number of entity synchronization issues within each application. This was in large part due to the differences in the terrain models used by each application.…”

Section: Limitationsmentioning

confidence: 99%

“…Differences in these models caused problems in matching camera views and entity positions from the UXV simulation with those views seen in GDIS2. Circumventing these issues for [4] required careful adjustments to the simulation and use of the terrain models to match all the necessary views and entities. Recent developments with VESS [2] should now allow the GDIS2 terrain models to be used with SimOCU and C2Node, thus eliminating most of these problems in future research.…”

Section: Limitationsmentioning

confidence: 99%

See 2 more Smart Citations

A Testbed for Exploring Human-Robot Interaction with Unmanned Aerial and Ground Vehicles

Flores

Martin

Durlach

2011

Engineering Psychology and Cognitive Ergonomics

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Over the last twenty years, the emerging roles of unmanned aerial/ ground vehicles in the U.S. military presented a number of different research opportunities in usability and training, ranging from robotic control interfaces to human-robot team collaboration. In this paper we present a testbed that we developed as a flexible software platform to explore a variety of training and coordination issues with UXVs for military application.

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Section: Automated Feedback Systemmentioning

confidence: 58%

Section: Limitationsmentioning

confidence: 99%

Section: Limitationsmentioning

confidence: 99%

See 1 more Smart Citation

A Testbed for Exploring Human-Robot Interaction with Unmanned Aerial and Ground Vehicles

Flores

Martin

Durlach

2011

Engineering Psychology and Cognitive Ergonomics

Self Cite

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“…Crespo et al (2016) built a VR drone simulator based on arm gestures with the aim of improving the health and quality of the elderly population. Durlach et al (2010) developed a prototype training procedure that not only teaches piloting skills but also demonstrates employment tactics, mission planning and coordination. Nguyen et al (2019) proposed a Web-based VR drone simulator based on real-world map data to assist operators in avoiding drone-associated building crashes and ensure safe drone landing.…”

Section: Introductionmentioning

confidence: 99%

DroneSim: a VR-based flight training simulator for drone-mediated building inspections

Albeaino

Eiris

Gheisari

et al. 2021

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Purpose This study aims to explore DroneSim, a virtual reality (VR)-based flight training simulator, as an alternative for real-world drone-mediated building inspection training. Design/methodology/approach Construction, engineering and management students were asked to pilot drones in the VR-based DroneSim space and perform common flight operations and inspection tasks within the spatiotemporal context of a building construction project. Another student group was also recruited and asked to perform a similar building inspection task in real world. The National Aeronautics and Space Administration (NASA)–Task Load Index (TLX) survey was used to assess students’ inflight workload demand under both Real and DroneSim conditions. Post-assessment questionnaires were also used to analyze students’ feedback regarding the usability and presence of DroneSim for drone building inspection training. Findings None of the NASA–TLX task load levels under real and DroneSim conditions were highly rated by students, and both groups experienced comparable drone-building inspection training. Students perceived DroneSim positively and found the VR experience stimulating. Originality/value This study’s contribution is twofold: to better understand the development stages involved in the design of a VR-based drone flight training simulator, specifically for building inspection tasks; and to improve construction students’ drone operational and flight training skills by offering them the opportunity to enhance their drone navigation skills in a risk-free, repeatable yet realistic environment. Such contributions ultimately pave the way for better integration of drone-mediated building inspection training in construction education while meeting industry needs.

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Adaptive and Nonadaptive Training Technology for Small Unmanned Aerial System Employment

Cited by 2 publications

References 9 publications

A Testbed for Exploring Human-Robot Interaction with Unmanned Aerial and Ground Vehicles

A Testbed for Exploring Human-Robot Interaction with Unmanned Aerial and Ground Vehicles

DroneSim: a VR-based flight training simulator for drone-mediated building inspections

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