Visual-Inertial Odometry on Chip: An Algorithm-and-Hardware Co-design Approach

Autonomous navigation of miniaturized robots (e.g., nano/pico aerial vehicles) is currently a grand challenge for robotics research, due to the need of processing a large amount of sensor data (e.g., camera frames) with limited on-board computational resources. In this paper we focus on the design o...

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Bibliographic Details
Main Authors: Zhang, Zhengdong (Contributor), Suleiman, Amr AbdulZahir (Contributor), Carlone, Luca (Contributor), Sze, Vivienne (Contributor), Karaman, Sertac (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Aeronautics and Astronautics (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Microsystems Technology Laboratories (Contributor)
Format: Article
Language:English
Published: 2017-06-01T21:09:22Z.
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Summary:Autonomous navigation of miniaturized robots (e.g., nano/pico aerial vehicles) is currently a grand challenge for robotics research, due to the need of processing a large amount of sensor data (e.g., camera frames) with limited on-board computational resources. In this paper we focus on the design of a visual-inertial odometry (VIO) system in which the robot estimates its ego-motion (and a landmark-based map) from on- board camera and IMU data. We argue that scaling down VIO to miniaturized platforms (without sacrificing performance) requires a paradigm shift in the design of perception algorithms, and we advocate a co-design approach in which algorithmic and hardware design choices are tightly coupled. Our contribution is four-fold. First, we discuss the VIO co-design problem, in which one tries to attain a desired resource-performance trade-off, by making suitable design choices (in terms of hardware, algorithms, implementation, and parameters). Second, we characterize the design space, by discussing how a relevant set of design choices affects the resource-performance trade-off in VIO. Third, we provide a systematic experiment-driven way to explore the design space, towards a design that meets the desired trade-off. Fourth, we demonstrate the result of the co-design process by providing a VIO implementation on specialized hardware and showing that such implementation has the same accuracy and speed of a desktop implementation, while requiring a fraction of the power.
United States. Air Force Office of Scientific Research. Young Investigator Program (FA9550-16-1-0228)
National Science Foundation (U.S.) (NSF CAREER 1350685)