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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
Summary
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.
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.
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