skip to main content
Explore Scholarly Publications and Datasets in the NSF-PAR

Title: Recreating Bat Behavior on Quad-Rotor UAVs—A Simulation Approach
We develop an effective computer model to simulate sensing environments that consist of natural trees. The simulated environments are random and contain full geometry of the tree foliage. While this simulated model can be used as a general platform for studying the sensing mechanism of different flying species, our ultimate goal is to build bat-inspired Quad-rotor UAVs—UAVs that can recreate bat’s flying behavior (e.g., obstacle avoidance, path planning) in dense vegetation. To this end, we also introduce an foliage echo simulator that can produce simulated echoes by mimicking bat’s biosonar. In our current model, a few realistic model choices or assumptions are made. First, in order to create natural looking trees, the branching structures of trees are modeled by L-systems, whereas the detailed geometry of branches, subbranches and leaves is created by randomizing a reference tree in a CAD object file. Additionally, the foliage echo simulator is simplified so that no shading effect is considered. We demonstrate our developed model by simulating real-world scenarios with multiple trees and compute the corresponding impulse responses along a Quad-rotor trajectory.
Authors:
; ; ; ; ;
Award ID(s):
1762577
Publication Date:
NSF-PAR ID:
10157883
Journal Name:
The Thirty-Third International FLAIRS Conference (FLAIRS-33)
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; ( , Sensors)
    Unmanned aerial vehicles (UAVs) have shown great potential in various applications such as surveillance, search and rescue. To perform safe and efficient navigation, it is vitally important for a UAV to evaluate the environment accurately and promptly. In this work, we present a simulation study for the estimation of foliage distribution as a UAV equipped with biosonar navigates through a forest. Based on a simulated forest environment, foliage echoes are generated by using a bat-inspired bisonar simulator. These biosonar echoes are then used to estimate the spatial distribution of both sparsely and densely distributed tree leaves. While a simple batchmore »processing method is able to estimate sparsely distributed leaf locations well, a wavelet scattering technique coupled with a support vector machine (SVM) classifier is shown to be effective to estimate densely distributed leaves. Our approach is validated by using multiple setups of leaf distributions in the simulated forest environment. Ninety-seven percent accuracy is obtained while estimating thickly distributed foliage.« less
  2. ; ; ; ( , Journal of experimental biology)
    To navigate in the natural environment, animals must adapt their locomotion in response to environmental stimuli. The echolocating bat relies on auditory processing of echo returns to represent its surroundings. Recent studies have shown that echo flow patterns influence bat navigation, but the acoustic basis for flight path selection remains unknown. To investigate this problem, we released bats in a flight corridor with walls constructed of adjacent individual wooden poles, which returned cascades of echoes to the flying bat. We manipulated the spacing and echo strength of the poles comprising each corridor side, and predicted that bats would adapt theirmore »flight paths to deviate toward the corridor side returning weaker echo cascades. Our results show that the bat’s trajectory through the corridor was not affected by the intensity of echo cascades. Instead, bats deviated toward the corridor wall with more sparsely spaced, highly reflective poles, suggesting that pole spacing, rather than echo intensity, influenced bat flight path selection. This result motivated investigation of the neural processing of echo cascades. We measured local evoked auditory responses in the bat inferior colliculus to echo playback recordings from corridor walls constructed of sparsely and densely spaced poles. We predicted that evoked neural responses would be discretely modulated by temporally distinct echoes recorded from the sparsely spaced pole corridor wall, but not by echoes from the more densely spaced corridor wall. The data confirm this prediction and suggest that the bat’s temporal resolution of echo cascades may drive its flight behavior in the corridor.« less
  3. ; ; ( , eLife)
    Essential to spatial orientation in the natural environment is a dynamic representation of direction and distance to objects. Despite the importance of 3D spatial localization to parse objects in the environment and to guide movement, most neurophysiological investigations of sensory mapping have been limited to studies of restrained subjects, tested with 2D, artificial stimuli. Here, we show for the first time that sensory neurons in the midbrain superior colliculus (SC) of the free-flying echolocating bat encode 3D egocentric space, and that the bat’s inspection of objects in the physical environment sharpens tuning of single neurons, and shifts peak responses tomore »represent closer distances. These findings emerged from wireless neural recordings in free-flying bats, in combination with an echo model that computes the animal’s instantaneous stimulus space. Our research reveals dynamic 3D space coding in a freely moving mammal engaged in a real-world navigation task.« less
  4. ; ; ( , Proceedings of the National Academy of Sciences)

    Unlike other predators that use vision as their primary sensory system, bats compute the three-dimensional (3D) position of flying insects from discrete echo snapshots, which raises questions about the strategies they employ to track and intercept erratically moving prey from interrupted sensory information. Here, we devised an ethologically inspired behavioral paradigm to directly test the hypothesis that echolocating bats build internal prediction models from dynamic acoustic stimuli to anticipate the future location of moving auditory targets. We quantified the direction of the bat’s head/sonar beam aim and echolocation call rate as it tracked a target that moved across its sonarmore »field and applied mathematical models to differentiate between nonpredictive and predictive tracking behaviors. We discovered that big brown bats accumulate information across echo sequences to anticipate an auditory target’s future position. Further, when a moving target is hidden from view by an occluder during a portion of its trajectory, the bat continues to track its position using an internal model of the target’s motion path. Our findings also reveal that the bat increases sonar call rate when its prediction of target trajectory is violated by a sudden change in target velocity. This shows that the bat rapidly adapts its sonar behavior to update internal models of auditory target trajectories, which would enable tracking of evasive prey. Collectively, these results demonstrate that the echolocating big brown bat integrates acoustic snapshots over time to build prediction models of a moving auditory target’s trajectory and enable prey capture under conditions of uncertainty.

    « less
  5. ; ; ; ; ; ( , Acoustics)
    Ultrasonic bat detectors are useful for research and monitoring purposes to assess occupancy and relative activity of bat communities. Environmental “clutter” such as tree boles and foliage can affect the recording quality and identification of bat echolocation calls collected using ultrasonic detectors. It can also affect the transmission of calls and recognition by bats when using acoustic lure devices to attract bats to mist-nets. Bat detectors are often placed in forests, yet automatic identification programs are trained on call libraries using echolocation passes recorded largely from open spaces. Research indicates that using clutter-recorded calls can increase classification accuracy for somemore »bat species and decrease accuracy for others, but a detailed understanding of how clutter impacts the recording and identification of echolocation calls remains elusive. To clarify this, we experimentally investigated how two measures of clutter (i.e., total basal area and number of stems of simulated woody growth, as well as recording angle) affected the recording and classification of a synthesized echolocation signal under controlled conditions in an anechoic chamber. Recording angle (i.e., receiver position relative to emitter) significantly influenced the probability of correct classification and differed significantly for many of the call parameters measured. The probability of recording echo pulses was also a function of clutter but only for the detector angle at 0° from the emitter that could receive deflected pulses. Overall, the two clutter metrics were overshadowed by proximity and angle of the receiver to the sound source but some deviations from the synthesized call in terms of maximum, minimum, and mean frequency parameters were observed. Results from our work may aid efforts to better understand underlying environmental conditions that produce false-positive and -negative identifications for bat species of interest and how this could be used to adjust survey accuracy estimates. Our results also help pave the way for future research into the development of acoustic lure technology by exploring the effects of environmental clutter on ultrasound transmission.« less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email