scholarly journals Mobile Robots for Harsh Environments: Lessons Learned from Field Experiments

Author(s):  
Eric L. Akers ◽  
Richard S. Stansbury ◽  
Torry L. Akins ◽  
Arvin Agah
Author(s):  
Anthony L. Baker ◽  
Sean M. Fitzhugh ◽  
Daniel E. Forster ◽  
Kristin E. Schaefer

The development of more effective human-autonomy teaming (HAT) will depend on the availability of validated measures of their performance. Communication provides a critical window into a team’s interactions, states, and performance, but much remains to be learned about how to successfully carry over communication measures from the human teaming context to the HAT context. Therefore, the purpose of this paper is to discuss the implementation of three communication assessment methodologies used for two Wingman Joint Capabilities Technology Demonstration field experiments. These field experiments involved Soldiers and Marines maneuvering vehicles and engaging in live-fire target gunnery, all with the assistance of intelligent autonomous systems. Crew communication data were analyzed using aggregate communication flow, relational event models, and linguistic similarity. We discuss how the assessments were implemented, what they revealed about the teaming between humans and autonomy, and lessons learned for future implementation of communication measurement approaches in the HAT context.


2016 ◽  
Vol 38 (1) ◽  
Author(s):  
Marc Keuschnigg ◽  
Tobias Wolbring

AbstractThis paper discusses social mechanisms of discrimination and reviews existing field experimental designs for their identification. We first explicate two social mechanisms proposed in the literature, animus-driven and statistical discrimination, to explain differential treatment based on ascriptive characteristics. We then present common approaches to study discrimination based on observational data and laboratory experiments, discuss their strengths and weaknesses, and elaborate why unobtrusive field experiments are a promising complement. However, apart from specific methodological challenges, well-established experimental designs fail to identify the mechanisms of discrimination. Consequently, we introduce a rapidly growing strand of research which actively intervenes in market activities varying costs and information for potential perpetrators to identify causal pathways of discrimination. We end with a summary of lessons learned and a discussion of challenges that lie ahead.


2014 ◽  
Vol 34 (2) ◽  
pp. 191-195 ◽  
Author(s):  
Faisal Khan ◽  
Salim Ahmed ◽  
Ming Yang ◽  
Seyed Javad Hashemi ◽  
Susan Caines ◽  
...  

Author(s):  
Amir R. Nejad ◽  
Jone Torsvik

AbstractThis paper presents lessons learned from own research studies and field experiments with drivetrains on floating wind turbines over the last ten years. Drivetrains on floating support structures are exposed to wave-induced motions in addition to wind loading and motions. This study investigates the drivetrain-floater interactions from two different viewpoints: how drivetrain impacts the sub-structure design; and how drivetrain responses and life are affected by the floater and support structure motion. The first one is linked to the drivetrain technology and layout, while the second question addresses the influence of the wave-induced motion. The results for both perspectives are presented and discussed. Notably, it is highlighted that the effect of wave induced motions may not be as significant as the wind loading on the drivetrain responses particularly in larger turbines. Given the limited experience with floating wind turbines, however, more research is needed. The main aim with this article is to synthesize and share own research findings on the subject in the period since 2009, the year that the first full-scale floating wind turbine, Hywind Demo, entered operation in Norway.


2017 ◽  
Vol 6 (2) ◽  
pp. 179-196 ◽  
Author(s):  
Jingwen Zhang ◽  
Christopher Calabrese ◽  
Jieyu Ding ◽  
Mingxuan Liu ◽  
Biying Zhang

As smartphone’s computing power continues to grow and as mobile applications (apps) continue to dominate digital engagement, apps have become a new frontier for advancing field experiment methodology. Using apps may help researchers to scale up the reach, precisely control randomization and experiment materials, collect a variety of objective and self-reported data over time, and more conveniently replicate and adapt an experiment. We performed a systematic review on field experiments involving apps published between 2007 and 2017. Seven databases were scanned using a predefined search strategy. The database search retrieved 4,810 citations; 101 articles met the inclusion criteria. Our review suggests that scholars have only started to employ apps in field experiments in the last 4 years. Most studies only used apps as an experiment treatment instead of an experiment platform; therefore, researchers have yet to fully leverage the advantages. Almost all studies were from the health research domain and 77.2% used randomized controlled trial design. Only 7 studies utilized smartphone sensors for collecting data. Only one study reported cost and ethical concerns regarding using apps for the experiment. Given these findings, we reported a case study that targeted a minority racial group and leveraged the advantages of apps as an experiment platform and as a data collection tool to illustrate practical challenges and lessons learned regarding time, financial cost, and technical support. In conclusion, we suggest apps provide new ways to study causal mechanisms with experiment big data. Limitations of generalizability, retention, and design quality were discussed as well.


PLoS ONE ◽  
2015 ◽  
Vol 10 (2) ◽  
pp. e0118560 ◽  
Author(s):  
Kayla M. Hardwick ◽  
Luke J. Harmon ◽  
Scott D. Hardwick ◽  
Erica Bree Rosenblum

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