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首页> 外文期刊>Journal of Intelligent & Robotic Systems: Theory & Application >Slope Perception from Monoscopic Field Images: Applications to Mobile Robot Navigation
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Slope Perception from Monoscopic Field Images: Applications to Mobile Robot Navigation

机译:单视场图像的坡度感知:在移动机器人导航中的应用

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摘要

When remotely navigating a mobile robot, operators must estimate the slope of local terrain in order to avoid areas that are too steep to climb or that slope so steeply downward that the operator would lose control of the rover. Although many rovers are equipped with sensor systems to aid the operator in this task, it is sometimes necessary to estimate slopes from two-dimensional images, either when planning operations or when the operator wishes to monitor the results of a sensor system. This experiment compares the operator's estimates of the slope in Martian terrain with the actual slope determined from three-dimensional data. The ten participants overestimated the slope of the indicated regions by an average of 19° (SD16°). An analytic model of the error, based on psychophysical analysis, accurately predicts the average magnitude of the errors. Implementation of this model eliminates an average amount of participant error. However, the large estimate variance within and between participants and images still poses a challenge for accurate slope estimation.
机译:在远程导航移动机器人时,操作员必须估算当地地形的坡度,以避免避开太陡而无法攀爬或坡度太陡的区域,以免操作员失去对流动站的控制。尽管许多流动站都配备有传感器系统以帮助操作员完成此任务,但有时在计划操作或操作员希望监视传感器系统结果时,有必要根据二维图像估算坡度。该实验将操作员对火星地形坡度的估计值与根据三维数据确定的实际坡度进行比较。十名参与者将指示区域的斜率平均高估了19°(SD16°)。基于心理物理分析的错误分析模型可以准确预测错误的平均幅度。该模型的实施消除了参与者错误的平均数量。但是,参与者和图像之间以及参与者与图像之间的较大估计方差仍然对准确的斜率估计提出了挑战。

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