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Hart S.,TRACLabs Inc | Dinh P.,Oceaneering Space Systems | Hambuchen K.,NASA
Proceedings - IEEE International Conference on Robotics and Automation | Year: 2015

This paper introduces the Affordance Template ROS package for quickly programming, adjusting, and executing robot applications in the ROS RViz environment. This package extends the capabilities of RViz interactive markers [1] by allowing an operator to specify multiple end-effector waypoint locations and grasp poses in object-centric coordinate frames and to adjust these waypoints in order to meet the run-time demands of the task (specifically, object scale and location). The Affordance Template package stores task specifications in a robot-agnostic JSON description format such that it is trivial to apply a template to a new robot. As such, the Affordance Template package provides a robot-generic ROS tool appropriate for building semi-autonomous, manipulation-based applications. Affordance Templates were developed by the NASA-JSC DARPA Robotics Challenge (DRC) team and have since successfully been deployed on multiple platforms including the NASA Valkyrie and Robonaut 2 humanoids, the University of Texas Dreamer robot and the Willow Garage PR2. In this paper, the specification and implementation of the affordance template package is introduced and demonstrated through examples for wheel (valve) turning, pick-and-place, and drill grasping, evincing its utility and flexibility for a wide variety of robot applications. © 2015 IEEE.

Murphy R.R.,Texas A&M University | Schreckenghost D.,TRACLabs Inc
ACM/IEEE International Conference on Human-Robot Interaction | Year: 2013

This paper examines 29 papers that have proposed or applied metrics for human-robot interaction. The 42 metrics are categorized as to the object being directly measured: the human (7), the robot (6), or the system (29). Systems metrics are further subdivided into productivity, efficiency, reliability, safety, and coactivity. While 42 seems to be a large set, many metrics do not have a functional, or generalizable, mechanism for measuring that feature. In practice, metrics for system interactions are often inferred through observations of the robot or the human, introducing noise and error in analysis. The metrics do not completely capture the impact of autonomy on HRI as they typically focus on the agents, not the capabilities. As a result the current metrics are not helpful for determining what autonomous capabilities and interactions are appropriate for what tasks. © 2013 IEEE.

Fong T.,NASA | Abercromby A.,Wyle | Bualat M.G.,NASA | Deans M.C.,NASA | And 5 more authors.
Acta Astronautica | Year: 2010

Robotic reconnaissance ("recon") has the potential to significantly improve scientific and technical return from lunar surface exploration. In particular, robotic recon can be used to improve traverse planning, reduce operational risk, and increase crew productivity. To study how robotic recon can benefit human exploration, we recently conducted a field experiment at Black Point Lava Flow (BPLF), Arizona. In our experiment, a simulated ground control team at NASA Ames teleoperated a planetary rover to scout geology traverses at BPLF. The recon data were then used to plan revised traverses. Two-man crews subsequently performed both types of traverses using the NASA "Lunar Electric Rover" (LER) and simulated extra-vehicular activity (EVA) suits. This paper describes the design of our experiment, presents our results, and discusses directions for future research. © 2010 Elsevier Ltd. All rights reserved.

Bell S.,TRACLabs Inc | Bonasso P.,TRACLabs Inc | Boddy M.,Adventium Labs | Kortenkamp D.,TRACLabs Inc | Schreckenghost D.,TRACLabs Inc
Communications in Computer and Information Science | Year: 2015

In this paper, we describe a set of software tools called the PRIDE ONTOlogy Editor (PRONTOE) and a methodology that allows system operators and domain experts to build and maintain ontologies of their systems with no explicit understanding of the underlying ontology representation. We present three case studies: one using NASA flight controllers, one using the DARPA Robotic Challenge, and one using unmanned vehicles. © Springer-Verlag Berlin Heidelberg 2015.

Bell S.,TRACLabs Inc | Kortenkamp D.,TRACLabs Inc | Zaientz J.,Soar Technology, Inc.
SAE International Journal of Aerospace | Year: 2011

A Lunar habitat will be highly sensored and generate large amounts of data or telemetry. For this data to be useful to humans monitoring these systems and to automated algorithms controlling these systems it will need to be converted into more abstract data. This abstracted data will reflect the trends, states and characteristics of the systems and their environments. Currently this data abstraction process is manual and ad hoc. We are developing a Data Abstraction Architecture (DAA) that allows engineers to design software processes that iteratively convert habitat data into higher and higher levels of abstraction. The DAA is a series of mathematical or logical transformations of telemetry data to provide appropriate inputs from a hardware system to a hardware system controller, system engineer, or crew. The DAA also formalizes the relationships between data and control and the relationships between the data themselves. We have connected our Data Abstraction Architecture to a simulation of a Lunar habitat in order to test its ability to aid in the monitoring and control functions. © 2009 SAE International.

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