Optical flow sensing and the inverse perception problem for flying bats

Kong, Zhaodan; Özcimder, Kayhan; Fuller, Nathan W.; Greco, Alison; Theriault, Diane; Wu, Zheng; Kunz, Thomas; Betke, Margrit; Baillieul, John

doi:10.1109/cdc.2013.6760112

Cited by 9 publications

(5 citation statements)

References 28 publications

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“…Each night they emerge in small groups after sunset [ 27 ]. They are insectivores and use echolocation as their primary means of sensing, although vision may also play a role in navigation [ 10 ]. An average bat in this species is 0.1 m long with a wingspan of 0.3 m, weighs 12 g, and has a cruising speed of 5.5–6.6 m s −1 [ 27 , 28 ].…”

Section: Methodsmentioning

confidence: 99%

“…The membership of, and interactions within, these smaller groups may be dependent on a metric distance, for example, the zonal model of shoaling fish [ 7 ], or a topological distance, as in the model of flocking starlings [ 8 ]. Models of perception have also been developed to investigate the use of optic flow in birds [ 9 ] and bats [ 10 ] and even visual tracking to aid collision avoidance in insects [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

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Using collision cones to assess biological deconfliction methods

Brace

Hedrick

Theriault

et al. 2016

J. R. Soc. Interface.

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Biological systems consistently outperform autonomous systems governed by engineered algorithms in their ability to reactively avoid collisions. To better understand this discrepancy, a collision avoidance algorithm was applied to frames of digitized video trajectory data from bats, swallows and fish (Myotis velifer, Petrochelidon pyrrhonota and Danio aequipinnatus). Information available from visual cues, specifically relative position and velocity, was provided to the algorithm which used this information to define collision cones that allowed the algorithm to find a safe velocity requiring minimal deviation from the original velocity. The subset of obstacles provided to the algorithm was determined by the animal's sensing range in terms of metric and topological distance. The algorithmic calculated velocities showed good agreement with observed biological velocities, indicating that the algorithm was an informative basis for comparison with the three species and could potentially be improved for engineered applications with further study.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Using collision cones to assess biological deconfliction methods

Brace

Hedrick

Theriault

et al. 2016

J. R. Soc. Interface.

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“…The optical flow based navigation discussed in [8], [9] [10], and [11] exploits visual cues based on time-to-transit (sometimes referred to in the computer vision and visual psychology literature as timeto-contact, [13]). Time-to-transit (referred to in the literature as tau-and frequently denoted by the symbol τ ) is a perceived quantity that is believed to be computable in the visual cortex as animals move about their environments.…”

Section: Idealized Optical Flow Based On Two and Many Pixelsmentioning

confidence: 99%

“…In such cases, algorithms that exploit alternative environmental cues are invoked. Some of these are discussed in [9,11], and others are the focus of ongoing research. Continuing with analysis of highly idealized models, in the next section we consider the benefits of control designs for systems with relatively high dimensional input and output spaces.…”

Section: Remarkmentioning

confidence: 99%

“…The overarching motivation for the research is the need for foundational principles and trustworthy algorithms to support autonomous mobility. A particular line of inquiry has been focused on the use of optical flow sensing to generate steering commands for both air and ground vehicles, [8,9,10,11]. Leveraging the capabilities of feature detectors, descriptors, and matchers that are now available in the OpenCV corpus ( [3]), the research is aimed at understanding how to focus attention so as to mitigate the uncertainties of visual perception.…”

Section: Introductionmentioning

confidence: 99%

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Perceptual Control with Large Feature and Actuator Networks

Baillieul¹

2019

2019 IEEE 58th Conference on Decision and Control (CDC)

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This paper discusses elements of a control theory of systems comprised of networks of simple agents that collectively achieve sensing and actuation goals despite having strictly limited capability when acting alone. The goal is to understand sensorimotor feedback control in which streams of data come from large arrays of sensors (e.g. photo-receptors in the eye) and actuation requires coordination of large numbers of actuators (e.g. motor neurons). The context for this work is set by consideration of a stylized problem of robot navigation that uses optical flow as sensed by two idealized and precise photoreceptors. A robust steering law in this setting establishes a foundation for exploiting optical flow based on averaged noisy inputs from large numbers of imprecise sensing elements. Taking inspiration from neurobiology, the challenges of actuator and sensor intermittency are discussed as are learning actuator coordination strategies. It is shown that there are advantages in having large numbers of control inputs and outputs. The results will be shown to make contact with ideas from control communication complexity and the standard parts problem.

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Data Association for Multi-Object Visual Tracking

Betke

2017

Synthesis Lectures on Computer Vision

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Optical flow sensing and the inverse perception problem for flying bats

Cited by 9 publications

References 28 publications

Using collision cones to assess biological deconfliction methods

Using collision cones to assess biological deconfliction methods

Perceptual Control with Large Feature and Actuator Networks

Data Association for Multi-Object Visual Tracking

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