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arXiv 1810.08704cs.RO

RaD-VIO: Rangefinder-aided Downward Visual-Inertial Odometry

The Robotics Institute, Carnegie Mellon University(卡内基梅隆大学机器人研究所)

Bo Fu, Kumar Shaurya Shankar, Nathan Michael

英文摘要:

State-of-the-art forward facing monocular visual-inertial odometry algorithms are often brittle in practice, especially whilst dealing with initialisation and motion in directions that render the state unobservable. In such cases having a reliable complementary odometry algorithm enables robust and resilient flight. Using the common local planarity assumption, we present a fast, dense, and direct frame-to-frame visual-inertial odometry algorithm for downward facing cameras that minimises a joint cost function involving a homography based photometric cost and an IMU regularisation term. Via extensive evaluation in a variety of scenarios we demonstrate superior performance than existing state-of-the-art downward facing odometry algorithms for Micro Aerial Vehicles (MAVs).

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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