Using the Neural Circuit of the Insect Central Complex for Path Integration on a Micro Aerial Vehicle

Stankiewicz, Jan; Webb, Barbara

doi:10.1007/978-3-030-64313-3_31

Cited by 3 publications

(4 citation statements)

References 14 publications

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“…A histogram of the homing errors for each trial is included in figure 6(d). The worst case homing error is 80 cm which represents a significant reduction compared with PI circuits which are likely to produce errors in the order of tens of meters [59].…”

Section: Simulated Implementation Tests 4221 Batch Testingmentioning

confidence: 99%

Looking down: a model for visual route following in flying insects

Stankiewicz

Webb

2021

Bioinspir. Biomim.

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Insect visual navigation is often assumed to depend on panoramic views of the horizon, and how these change as the animal moves. However, it is known that honey bees can visually navigate in flat, open meadows where visual information at the horizon is minimal, or would remain relatively constant across a wide range of positions. In this paper we hypothesise that these animals can navigate using view memories of the ground. We find that in natural scenes, low resolution views from an aerial perspective of ostensibly self-similar terrain (e.g. within a field of grass) provide surprisingly robust descriptors of precise spatial locations. We propose a new visual route following approach that makes use of transverse oscillations to centre a flight path along a sequence of learned views of the ground. We deploy this model on an autonomous quadcopter and demonstrate that it provides robust performance in the real world on journeys of up to 30 m. The success of our method is contingent on a robust view matching process which can evaluate the familiarity of a view with a degree of translational invariance. We show that a previously developed wavelet based bandpass orientated filter approach fits these requirements well, exhibiting double the catchment area of standard approaches. Using a realistic simulation package, we evaluate the robustness of our approach to variations in heading direction and aircraft height between inbound and outbound journeys. We also demonstrate that our approach can operate using a vision system with a biologically relevant visual acuity and viewing direction.

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Section: Simulated Implementation Tests 4221 Batch Testingmentioning

confidence: 99%

Looking down: a model for visual route following in flying insects

Stankiewicz

Webb

2021

Bioinspir. Biomim.

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“…More recently, these deep brain models have been augmented with biologically plausible perception systems capable of generating a compass signal from polarised light accurate to less than one degree in ideal conditions [104] through a matched-filter-like process [105]. Robotic implementations of these models have been instantiated and provide the necessary real-world verification of hypotheses and inspiration for engineers [106][107][108][109].…”

Section: Mental Faculties: Revealing the Neural Basis Of Invertebrate...mentioning

confidence: 99%

“…CC BY 4.0. (bottom row, left column) Reproduced from [108], with permission from Springer Nature. (top row, right column, desert photo) Image taken by Michael Mangan.…”

Section: Mental Faculties: Revealing the Neural Basis Of Invertebrate...mentioning

confidence: 99%

A virtuous cycle between invertebrate and robotics research: perspective on a decade of Living Machines research

et al. 2023

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Many invertebrates are ideal model systems on which to base robot design principles due to their success in solving seemingly complex tasks across domains while possessing smaller nervous systems than vertebrates. Three areas are particularly relevant for robot designers: Research on flying and crawling invertebrates has inspired new materials and geometries from which robot bodies (their morphologies) can be constructed, enabling a new generation of softer, smaller, and lighter robots. Research on walking insects has informed the design of new systems for controlling robot bodies (their motion control) and adapting their motion to their environment without costly computational methods. And research combining wet and computational neuroscience with robotic validation methods has revealed the structure and function of core circuits in the insect brain responsible for the navigation and swarming capabilities (their mental faculties) displayed by foraging insects. The last decade has seen significant progress in the application of principles extracted from invertebrates, as well as the application of biomimetic robots to model and better understand how animals function. This Perspectives paper on the past 10 years of the Living Machines conference outlines some of the most exciting recent advances in each of these fields before outlining lessons gleaned and the outlook for the next decade of invertebrate robotic research.

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“…The conference is targeted at the intersection of research on novel life-like technologies inspired by natural systems, biomimetics, and research that seeks to interface biological and artificial systems to create biohybrid systems. This issue features a selection of the best research papers from the 2020 edition of the Living Machines conference (Vouloutsi et al 2020) [14], chosen by a panel of experts for publication in this special issue, including award-winning papers and posters (1st and 2nd place best papers by Cheng et al 2020 [11], and Meder et al 2020 [12]; 1st place best poster by Stankiewicz & Webb, 2020 [13]).…”

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confidence: 99%