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Quantitative Assessments of USARSim Accuracy

Stefano Carpin, Todor Stoyanov, Yashodhan Nevatia, Michael Lewis, J. Wang

Year
2006
Citations
67

Abstract

Abstract — Effective robotic simulation depends on accurate modeling of physics and the environment as well as the robot, itself. This paper describes validation studies examining feature extraction, WaveLan radio performance, and human interaction for the USARSim robotic simulation. All four feature extraction algorithms showed strong correspondences between data collected in simulation and from real robots. In each case data extracted from a well lit scene produced a closer match to data extracted from a simulated image than to camera data from a poorly lit scene. The radio simulation also performed well in validation showing levels of attenuation due to intervening walls that were similar to signal strengths measured in the modeled environment. The human-robot interaction experiments showed close correspondence between simulator and robots in performance affected by robot model, control mode and task difficulty. I.

Keywords

RobotComputer scienceFeature extractionArtificial intelligenceTask (project management)Feature (linguistics)Computer visionHuman–robot interactionAttenuationSIGNAL (programming language)

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