TCB-VIO: 焦点面バイナリ強調型密結合視覚慣性オドメトリ
TCB-VIO: Tightly-Coupled Focal-Plane Binary-Enhanced Visual Inertial Odometry
焦点面センサプロセッサ上で動作する高フレームレートの密結合VIOを提案し、従来手法を上回る性能を示した。
詳しい要約
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2. 先行研究と比べてどこがすごい？
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著者: Matthew Lisondra, Junseo Kim, Glenn Takashi Shimoda, Kourosh Zareinia, Sajad Saeedi
分類: cs.RO
原文アブストラクト
Vision algorithms can be executed directly on the image sensor when implemented on the next-generation sensors known as focal-plane sensor-processor arrays (FPSP)s, where every pixel has a processor. FPSPs greatly improve latency, reducing the problems associated with the bottleneck of data transfer from a vision sensor to a processor. FPSPs accelerate vision-based algorithms such as visual-inertial odometry (VIO). However, VIO frameworks suffer from spatial drift due to the vision-based pose estimation, whilst temporal drift arises from the inertial measurements. FPSPs circumvent the spatial drift by operating at a high frame rate to match the high-frequency output of the inertial measurements. In this paper, we present TCB-VIO, a tightly-coupled 6 degrees-of-freedom VIO by a Multi-State Constraint Kalman Filter (MSCKF), operating at a high frame-rate of 250 FPS and from IMU measurements obtained at 400 Hz. TCB-VIO outperforms state-of-the-art methods: ROVIO, VINS-Mono, and ORB-SLAM3.
