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Real-Time Egocentric Navigation Using 3D Sensing

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Machine Vision and Navigation

Abstract

This chapter proposes a hierarchical navigation system combining the benefits of perception space local planning and allocentric global planning. Perception space permits computationally efficient 3D collision checking, enabling safe navigation in environments that do not meet the conditions assumed by traditional navigation systems based on planar laser scans. Contributions include approaches for scoring and collision checking trajectories in perception space. Benchmarking results show the advantages of perception space collision checking over popular alternatives in the context of real-time local planning. Simulated experiments with multiple robotic platforms in several environments demonstrate the importance of 3D collision checking and the utility of a mixed representation hierarchical navigation system.

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Acknowledgement

This work was supported in part by NSF Awards #1400256 and #1849333.

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Authors and Affiliations

  1. Georgia Tech, School of Electrical and Computer Engineering, Atlanta, GA, USA

    Justin S. Smith, Fanzhe Lyu & Patricio A. Vela

  2. Georgia Tech, School of Mechanical Engineering, Atlanta, GA, USA

    Shiyu Feng

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  1. Justin S. Smith
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  2. Shiyu Feng
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  3. Fanzhe Lyu
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  4. Patricio A. Vela
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Correspondence to Patricio A. Vela .

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  1. Universidad Autónoma de Baja California, Mexicali, Baja California, Mexico

    Oleg Sergiyenko

  2. Universidad Autónoma de Baja California, Mexicali, Baja California, Mexico

    Wendy Flores-Fuentes

  3. Leuphana University of Lueneburg, Lueneburg, Low Saxony, Niedersachsen, Germany

    Paolo Mercorelli

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Smith, J.S., Feng, S., Lyu, F., Vela, P.A. (2020). Real-Time Egocentric Navigation Using 3D Sensing. In: Sergiyenko, O., Flores-Fuentes, W., Mercorelli, P. (eds) Machine Vision and Navigation. Springer, Cham. https://doi.org/10.1007/978-3-030-22587-2_14

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  • DOI: https://doi.org/10.1007/978-3-030-22587-2_14

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