Kyohei Otsu

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Identifying terrain type is crucial to safely operating planetary exploration rovers. Vision-based terrain classifiers, which are typically trained by thousands of labeled images using machine learning methods, have proven to be particularly successful. However, since planetary rovers are to boldly go where no one has gone before, training data are usually(More)
This paper proposes a novel method to estimate relative poses for a calibrated stereo camera. Three corresponding points in 3D space are theoretically required to recover unconstraint motion which has six degrees of freedom. The proposed method solves this problem with only two 3D points by exploiting a common reference direction between poses. Two points(More)
Estimating the position of a robot is an essential requirement for the autonomous mobile robots. Visual Odometry (VO) can play a key role in navigation tasks on the slippery natural terrain, which highly degrades the accuracy of Wheel Odometry (WO), without relying neither on other infrastructures nor any prior knowledge. A challenge of the VO system lies(More)
This paper describes a stereo visual odometry system for volcanic fields which lack visual features on the ground. There are several technical problems in untextured terrain including the diversity of terrain appearance, the lack of welltracked features on surfaces, and the limited computational resources of onboard computers. This paper tries to address(More)
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