Quantitative Assessments of USARSim Accuracy
Quantitative Assessments of USARSim Accuracy
复制标题
USARSim 准确性的定量评估
DOI：
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发表时间：
2006
期刊：
影响因子：
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通讯作者：
Jijun Wang
中科院分区：
文献类型：
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作者：
Stefano Carpin;Todor Stoyanov;Y. Nevatia;M. Lewis;Jijun Wang
有效的机器人模拟取决于对物理和环境以及机器人自身的精确建模。本文描述了针对美国救援机器人模拟（USARSim）的特征提取、无线局域网（WaveLan）无线电性能以及人机交互的验证研究。所有四种特征提取算法在模拟收集的数据和真实机器人的数据之间都显示出很强的一致性。在每种情况下，从光照良好的场景中提取的数据与从模拟图像中提取的数据相比，与从光照不佳的场景中的相机数据更为匹配。无线电模拟在验证中也表现良好，显示出由于中间墙壁导致的衰减程度与在建模环境中测量的信号强度相似。人机交互实验表明，在受机器人模型、控制模式和任务难度影响的性能方面，模拟器和机器人之间具有紧密的一致性。
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.