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Full text release has been delayed at the author's request until August 03, 2026

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Sensorimotor Models of Foraging Echolocating Bats

Nguyen, Thinh
http://orcid.org/0000-0001-8452-4853
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1721639784856218

Abstract Details

2024, PhD, University of Cincinnati, Engineering and Applied Science: Electrical Engineering.
Echolocating bats demonstrate sonar's remarkable ability to support various complex tasks, from navigating dense vegetation to foraging in flight. However, achieving these tasks using echolocation alone presents challenges due to the inherent limitations of sonar. Drawing inspiration from biological systems, we can narrow the performance gap between artificial and biological sonar. In this context, we develop behavior-based systems using sensorimotor loops and their interactions to accomplish the foraging task. We showcase a solution to the foraging task by training machine learning models to arbitrate between the approach and avoid sensorimotor loops using solely echoes as perception inputs. These models demonstrate a high success rate in foraging for insect-like targets and flower targets. In addition, they are robust against different arena geometries, traps, and noisy motor control. While arbitrating between the two sensorimotor loops proves effective, the system does not demonstrate attention to a single target, failing to investigate a flower target thoroughly. To address this, we develop a novel sensorimotor loop, termed the flower home-in loop, designed to guide nectarivorous bats toward a flower opening while maintaining attention on the target. The flower home-in loop perfectly performs when approaching the flower from the front. However, the performance gets worse when approaching the flower from other sides. Continuously re-estimating the target flower pose and updating the bat's path is a more robust strategy for the flower home-in loop in acoustically ambiguous scenarios. The flower home-in loop can also guide the bat toward the echoes from a flower's opening while being interfered with by echoes from nearby objects.
Dieter Vanderelst, Ph.D. (Committee Chair)
Ali Minai, Ph.D. (Committee Member)
Herbert Peremans, Ph.D M.A B.A. (Committee Member)
John Gallagher, Ph.D. (Committee Member)
Zachariah Fuchs, Ph.D. (Committee Member)
156 p.
Robotics
Echolocation; Sensorimotor models; Foraging; Machine Learning; Robotics; Air-sonar

Recommended Citations

Citations

  • Nguyen, T. (2024). Sensorimotor Models of Foraging Echolocating Bats [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1721639784856218

    APA Style (7th edition)

  • Nguyen, Thinh. Sensorimotor Models of Foraging Echolocating Bats. 2024. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1721639784856218.

    MLA Style (8th edition)

  • Nguyen, Thinh. "Sensorimotor Models of Foraging Echolocating Bats." Doctoral dissertation, University of Cincinnati, 2024. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1721639784856218

    Chicago Manual of Style (17th edition)

ucin1721639784856218
© 2024, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.