Measure (data warehouse)
Related papers: 20
About
A measure, in the context of data warehousing and robotics/AI analytics, is a quantifiable numerical value used to evaluate, compare, or optimize system performance across collected datasets. In robotics and AI, measures serve as the foundational metrics within data pipelines and analytical frameworks — capturing everything from a robot manipulator's dexterity and manipulability to human-robot trust levels, sensor accuracy, and navigation efficiency. These values are aggregated, filtered, and analyzed within structured data warehouses to support decision-making, system design, and performance benchmarking. For example, manipulability measures quantify how effectively a robotic arm can position its end-effector, while trust metrics evaluate collaboration quality between humans and autonomous systems. Measures are typically numerical facts that can be summed, averaged, or otherwise computed across dimensional axes such as time, robot configuration, or task type. They matter because they transform raw sensor readings and experimental observations into actionable insights, enabling engineers and researchers to systematically evaluate, calibrate, and improve robotic systems through principled, data-driven analysis.
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Top Cited Papers
Manipulability of Robotic Mechanisms
Tsuneo Yoshikawa
Citations: 2516 • 1985
Task-oriented optimal grasping by multifingered robot hands
Zexiang Li, S. Shankar Sastry
Citations: 473 • 1988
Nonsmooth Mechanics: Models, Dynamics and Control
Bernard Brogliato
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A general algorithm for robot formations using local sensing and minimal communication
Jakob Fredslund, Maja J. Matarić
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Searching in the Plane
Ricardo Baeza‐Yates, Joseph Culberson, Gregory J. E. Rawlins
Citations: 424 • 1993
Optimal motion planning for multiple robots having independent goals
Steven M. LaValle, Seth Hutchinson
Citations: 423 • 1998
Dynamic Map Building for an Autonomous Mobile Robot
John J. Leonard, Hugh Durrant‐Whyte, Ingemar J. Cox
Citations: 415 • 1992
A portable three-dimensional LIDAR-based system for long-term and wide-area people behavior measurement
Kenji Koide, Jun Miura, Emanuele Menegatti
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Dynamic manipulability of robot manipulators
T. Yoshikawa
Citations: 364 • 2005
Contact Sensing from Force Measurements
Antonio Bicchi, J. Kenneth Salisbury, David L. Brock
Citations: 305 • 1993
Measurement of trust in human-robot collaboration
Amos Freedy, Ewart deVisser, Gershon Weltman, Nicole Coeyman
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Manipulability and redundancy control of robotic mechanisms
T. Yoshikawa
Citations: 295 • 2005
Generalized picture distance measure and applications to picture fuzzy clustering
Lê Hoàng Sơn
Citations: 273 • 2016
Using infrared sensors for distance measurement in mobile robots
G. Benet, Francisco Blanes, José Simó, Pablo Fernández Pérez
Citations: 252 • 2002
Metrics for Evaluating Human-Robot Interactions
Michael A. Goodrich, Dan R. Olsen
Citations: 245 • 2003
Global A-Optimal Robot Exploration in SLAM
Robert B. Sim, Nicholas Roy
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A multidimensional conception and measure of human-robot trust
Bertram F. Malle, Daniel Ullman
Citations: 232 • 2020
An affective mobile robot educator with a full-time job
Illah Nourbakhsh, Judith Bobenage, S. Grange, Ron Lutz, Roland Meyer, Álvaro Soto
Citations: 228 • 1999
Determination of Optimal Measurement Configurations for Robot Calibration Based on Observability Measure
Jin-Hwan Borm, Chia-Hsiang Meng
Citations: 225 • 1991
Improved GelSight tactile sensor for measuring geometry and slip
Citations: 210 • 2017