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109522 |
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|a dc
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|a Zhang, Zhengdong
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|a Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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|a Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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|a Massachusetts Institute of Technology. Microsystems Technology Laboratories
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|a Sze, Vivienne
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|a Zhang, Zhengdong
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|a Suleiman, Amr AbdulZahir
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|a Carlone, Luca
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|a Sze, Vivienne
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|a Karaman, Sertac
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|a Suleiman, Amr AbdulZahir
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|a Carlone, Luca
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|a Sze, Vivienne
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|a Karaman, Sertac
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|a Visual-Inertial Odometry on Chip: An Algorithm-and-Hardware Co-design Approach
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|c 2017-06-01T21:09:22Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/109522
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|a 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.
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|a United States. Air Force Office of Scientific Research. Young Investigator Program (FA9550-16-1-0228)
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|a National Science Foundation (U.S.) (NSF CAREER 1350685)
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|a en_US
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|a Article
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|t Robotics: Science and Systems
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