UAV-guided navigation for ground robot tele-operation in a military reconnaissance environment

Chen, Jessie Y. C.

doi:10.1080/00140139.2010.500404

Cited by 86 publications

(55 citation statements)

References 21 publications

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“…U.S. Air Force scientists (Chappelle, McMillan, Novy, & McDonald, 2010;Chappelle, Novy, Randall, & McDonald, 2010) interviewed 53 subject matter experts about abilities that were critical to effective performance of UAS control tasks in terms of piloting and sensor operations; SpA was identified as an important factor for both tasks. Our previous research showed that individuals with greater SpA exhibited more effective visual scanning and target detection performance (Chen, 2010;Chen & Joyner, 2009;Chen & Terrence, 2008.…”

Section: Individual Differencesmentioning

confidence: 99%

“…Spatial ability (SpA) has been found to be a significant factor in certain visual display domains (Stanney & Salvendy, 1995), multitasking involving flight asset monitoring and management (Morgan et al, 2011), virtual environment navigation (Chen, Czerwinski, & Macredie, 2000), target search task (Chen, 2010;Chen & Joyner, 2009;Chen & Terrence, 2008, and robotics task performance (Cassenti, Kelley, Swoboda, & Patton, 2009;Lathan & Tracey, 2002). U.S. Air Force scientists (Chappelle, McMillan, Novy, & McDonald, 2010;Chappelle, Novy, Randall, & McDonald, 2010) interviewed 53 subject matter experts about abilities that were critical to effective performance of UAS control tasks in terms of piloting and sensor operations; SpA was identified as an important factor for both tasks.…”

Section: Individual Differencesmentioning

confidence: 99%

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Supervisory Control of Multiple Robots

2012

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Objective: A military multitasking environment was simulated to examine the effects of an intelligent agent, RoboLeader, on the performance of robotics operators.Background: The participants' task was to manage a team of ground robots with the assistance of RoboLeader, an intelligent agent capable of coordinating the robots and changing their routes on the basis of battlefield developments.Method: In the first experiment, RoboLeader was perfectly reliable; in the second experiment, RoboLeader's recommendations were manipulated to be either false-alarm prone or miss prone, with a reliability level of either 60% or 90%. The visual density of the targeting environment was manipulated by the presence or absence of friendly soldiers.Results: RoboLeader, when perfectly reliable, was helpful in reducing the overall mission times. The type of RoboLeader imperfection (false-alarm vs. miss prone) affected operators' performance of tasks involving visual scanning (target detection, route editing, and situation awareness). There was a consistent effect of visual density (clutter of the visual scene) for multiple performance measures. Participants' attentional control and video gaming experience affected their overall multitasking performance. In both experiments, participants with greater spatial ability consistently outperformed their low-spatial-ability counterparts in tasks that required effective visual scanning.Conclusion: Intelligent agents, such as RoboLeader, can benefit the overall human-robot teaming performance. However, the effects of type of agent unreliability, tasking requirements, and individual differences have complex effects on human-agent interaction.Application: The current results will facilitate the implementation of robots in military settings and will provide useful data to designs of systems for multirobot control.

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Section: Individual Differencesmentioning

confidence: 99%

Section: Individual Differencesmentioning

confidence: 99%

Supervisory Control of Multiple Robots

2012

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“…They have also found signifant use by the military [19,20]. In "Low-Cost Aerial Unit for Outdoor Inspection of Building Facades" the authors used a UAS equipped with a Microsoft Kinect sensor in order to collect geometric data from buildings [7].…”

Section: Uas Applications In Surveying Sensing and Scanningmentioning

confidence: 99%

Overcoming the Challenges of Using Unmanned Aircraft for Bridge Inspections

Hernández

2016

AIAA Atmospheric Flight Mechanics Conference

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Applications for small unmanned aerial vehicles have exploded over the past decade. Small size, maneuverability, low cost, and versatility enable utilization for applications not readily accessible by traditional manned aircraft, such as bridge inspections.However, the challenges associated with conducting inspections in a safe, cost efficient manner currently exceed the benefits of using an unmanned aircraft for inspection. The

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“…Rojo, Alczar, Lpez-Pichaco, & Nogales, 2003) and manipulators (Goertz, 1963;Howe & Kontarinis, 1994;D.-H. Kim, Kim, Kim, & Cha, 2001;C. Smith, Bratt, & Christensen, 2008) alike -through various input devices, from graphical interfaces (Paravati, Sanna, Lamberti, & Celozzi, 2011) to joysticks (C. H. Park & Howard, 2007) to motion capture (Hu, Meng, Liu, & Wang, 2003), and for various tasks, ranging from military reconnaissance (Chen, 2010;Kadous, Sheh, & Sammut, 2006) to telesurgery (Okamura, 2004) to caregiving at home (Labonte et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

Teleoperation with Intelligent and Customizable Interfaces

Dragan

Srinivasa

Lee

2013

Journal of Human-Robot Interaction

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In this paper, we explore a class of teleoperation problems where a user controls a sophisticated device (e.g. a robot) via an interface to perform a complex task. Teleoperation interfaces are fundamentally limited by the indirectness of the process, by the fact that the user is not physically executing the task. In this work, we study intelligent and customizable interfaces: these are interfaces that mediate the consequences of indirectness and make teleoperation more seamless. They are intelligent in that they take advantage of the robot's autonomous capabilities and assist in accomplishing the task. They are customizable in that they enable the users to adapt the retargetting function which maps their input onto the robot. Our studies support the advantages of such interfaces, but also point out the challenges they bring. We make three key observations. First, although assistance can greatly improve teleperation, the decision on how to provide assistance must be contextual. It must depend, for example, on the robot's confidence in its prediction of the user's intent. Second, although users do have the ability to provide intent-expressive input that simplifies the robot's prediction task, this ability can be hindered by kinematic differences between themselves and the robot. And third, although interface customization is important, it must be robust to poor examples from the user.

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UAV-guided navigation for ground robot tele-operation in a military reconnaissance environment

Cited by 86 publications

References 21 publications

Supervisory Control of Multiple Robots

Supervisory Control of Multiple Robots

Overcoming the Challenges of Using Unmanned Aircraft for Bridge Inspections

Teleoperation with Intelligent and Customizable Interfaces

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