Improving the Robustness of a Direct Visual Odometry Algorithm for Planetary Rovers

G. Martinez
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引用次数: 2

Abstract

An algorithm capable of computing the robot position by evaluating measurements of frame to frame intensity differences was extended to be able to detect outliers in the measurements to exclude them from the evaluation to perform the positioning, with the aim of improving its robustness in irregular terrain scenes, such as consisting of flat surfaces with stones on them. The images are taken by a camera firmly attached to the robot, tilted downwards, looking at the planetary surface. A measurement is detected as an outlier only if its intensity difference and linear intensity gradients can not be described by motion compensation. According to the experimental results, this modification reduced the positioning error by a factor of one third in difficult terrain, maintaining its positioning error, which resulted in an average of 1.8%, within a range of 0.15% and 2.5% of distance traveled, similar to those achieved by state of the art algorithms successfully used in robots here on earth and on Mars.
提高行星漫游者直接视觉里程计算法的鲁棒性
一种能够通过评估帧与帧之间的强度差异来计算机器人位置的算法进行了扩展,以能够检测测量中的异常值,从而将其排除在评估之外以执行定位,目的是提高其在不规则地形场景中的鲁棒性,例如由平坦的表面组成的石头。这些图像是由固定在机器人上的相机拍摄的,向下倾斜,观察行星表面。只有当测量值的强度差和线性强度梯度不能用运动补偿来描述时,才会被检测为异常值。根据实验结果,这种改进将复杂地形中的定位误差降低了三分之一,保持了其定位误差,平均定位误差为1.8%,在0.15%和2.5%的距离范围内,类似于在地球和火星上成功使用的最先进算法。
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