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PIRVS: An Advanced Visual-Inertial SLAM System with Flexible Sensor Fusion and Hardware Co-Design

Zhe Zhang, Shaoshan Liu, Grace Tsai, Hongbing Hu, Chen-Chi Chu, Feng Zheng

Year
2017
Citations
5
Access
Open access

Abstract

In this paper, we present the PerceptIn Robotics Vision System (PIRVS) system, a visual-inertial computing hardware with embedded simultaneous localization and mapping (SLAM) algorithm. The PIRVS hardware is equipped with a multi-core processor, a global-shutter stereo camera, and an IMU with precise hardware synchronization. The PIRVS software features a novel and flexible sensor fusion approach to not only tightly integrate visual measurements with inertial measurements and also to loosely couple with additional sensor modalities. It runs in real-time on both PC and the PIRVS hardware. We perform a thorough evaluation of the proposed system using multiple public visual-inertial datasets. Experimental results demonstrate that our system reaches comparable accuracy of state-of-the-art visual-inertial algorithms on PC, while being more efficient on the PIRVS hardware.

Keywords

Inertial measurement unitComputer scienceArtificial intelligenceComputer visionInertial frame of referenceSimultaneous localization and mappingShutterRoboticsSoftwareComputer hardware

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