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A simulation framework for bio-inspired sonar sensing with Unmanned Aerial Vehicles.

M Hassan Tanveer1, Xiaowei Wu2, Antony Thomas3

  • 1Department of Robotics & Mechatronics Engineering, Kennesaw State University, Marietta, Georgia, United States of America.

Plos One
|November 3, 2020
PubMed
Summary
This summary is machine-generated.

A new simulation framework generates realistic natural environments and biosonar echoes for training Unmanned Aerial Vehicles (UAVs). This tool aids in developing advanced robotic algorithms for biosonar-based navigation and sensing.

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Area of Science:

  • Robotics and Artificial Intelligence
  • Bioacoustics and Sensory Ecology

Background:

  • Biosonar-based Unmanned Aerial Vehicles (UAVs) require realistic training data.
  • Simulating natural environments and sensor echoes is computationally challenging.

Purpose of the Study:

  • To introduce a unified simulation framework for generating natural sensing environments and biosonar echoes.
  • To enable the training of robotic algorithms for biosonar-based UAVs.

Main Methods:

  • Utilized Lindenmayer systems and 3D CAD data for natural tree modeling.
  • Employed an inhomogeneous Poisson process for forest generation.
  • Developed a foliage echo simulator mimicking bat biosonar systems.

Main Results:

  • Generated rich sensory data with complete environmental information.
  • Simulated realistic forest environments with detailed foliage.
  • Produced biosonar echoes for static and dynamic UAV motion scenarios.

Conclusions:

  • The proposed framework provides a valuable tool for testing sensors and training robotic algorithms.
  • It specifically supports the development of bat-inspired UAVs for biosonar-based navigation.