Collision avoidance in biological systems using collision cones

Boardman, Beth; Hedrick, Tyson L.; Theriault, Diane; Fuller, Nathan W.; Betke, Margrit; Morgansen, Kristi A.

doi:10.1109/acc.2013.6580285

Cited by 14 publications

(3 citation statements)

References 25 publications

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“…In this work, we compare the collision avoidance trajectories of bats ( Myotis velifer ), birds ( Petrochelidon pyrrhonota ) and fish ( Danio aequipinnatus ) to those predicted by the DRCA algorithm. This paper presents an extension of the original DRCA algorithm from two to three dimensions and corrects a previous study done by Boardman et al [ 26 ], which performed a similar analysis by flattening the trajectories to two dimensions and applying the original DRCA algorithm. The three-dimensional analysis provides the algorithm with spatial information that corresponds more closely to the three-dimensional environments of the animals and eliminates ‘phantom conflicts’ created by two-dimensional conflict checking.…”

Section: Introductionsupporting

confidence: 73%

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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: Introductionsupporting

confidence: 73%

“…The cave bats were filmed in low light using three mid-infrared FLIR SC8000 cameras at a resolution of 1024 × 1024 pixels [ 26 ]. Camera calibration was performed for both bats and swallows (see below) by passing a 1 m long reference object through the shared field of view and applying a structure-from-motion algorithm [ 29 ].…”

Section: Methodsmentioning

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 research presented in this paper is part of a growing body of work aimed at understanding the sensorimotor motor control of flying animals. We refer to [11], [18], [1], and [4] for examples.…”

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confidence: 99%

Optical Flow Sensing and the Inverse Perception Problem for Flying Bats

Kong

Özcimder

Fuller

et al. 2013

Preprint

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The movements of birds, bats, and other flying species are governed by complex sensorimotor systems that allow the animals to react to stationary environmental features as well as to wind disturbances, other animals in nearby airspace, and a wide variety of unexpected challenges. The paper and talk will describe research that analyzes the three-dimensional trajectories of bats flying in a habitat in Texas. The trajectories are computed with stereoscopic methods using data from synchronous thermal videos that were recorded with high temporal and spatial resolution from three viewpoints. Following our previously reported work, we examine the possibility that bat trajectories in this habitat are governed by optical flow sensing that interpolates periodic distance measurements from echolocation. Using an idealized geometry of bat eyes, we introduce the concept of time-to-transit, and recall some research that suggests that this quantity is computed by the animals' visual cortex. Several steering control laws based on time-to-transit are proposed for an idealized flight model, and it is shown that these can be used to replicate the observed flight of what we identify as typical bats. Although the vision-based motion control laws we propose and the protocols for switching between them are quite simple, some of the trajectories that have been synthesized are qualitatively bat-like. Examination of the control protocols that generate these trajectories suggests that bat motions are governed both by their reactions to a subset of key feature points as well by their memories of where these feature points are located. I. INTORDUCTIONThis paper describes research aimed at using observed flight trajectories of a species of bats to understand the ways in which the animals use sensory perceptions of their environments

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