2017
DOI: 10.1016/j.asd.2017.08.001
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A lightweight, inexpensive robotic system for insect vision

Abstract: Designing hardware for miniaturized robotics which mimics the capabilities of flying insects is of interest, because they share similar constraints (i.e. small size, low weight, and low energy consumption). Research in this area aims to enable robots with similarly efficient flight and cognitive abilities. Visual processing is important to flying insects' impressive flight capabilities, but currently, embodiment of insect-like visual systems is limited by the hardware systems available. Suitable hardware is ei… Show more

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Cited by 9 publications
(5 citation statements)
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“…Good performance in most lighting circumstances, especially in low light, is one of the benefits of CCD image sensors because the WDR feature adjusts the exposure and the color to be faultless [69]. The video has no vibration effect, and the image contrast is better than CMOS.…”
Section: A) Advantages Of Ccd Imaging Sensormentioning
confidence: 99%
“…Good performance in most lighting circumstances, especially in low light, is one of the benefits of CCD image sensors because the WDR feature adjusts the exposure and the color to be faultless [69]. The video has no vibration effect, and the image contrast is better than CMOS.…”
Section: A) Advantages Of Ccd Imaging Sensormentioning
confidence: 99%
“…Due to the high frame rate, low weight and low energy consumption the module is ideally suited to be placed on fast moving robotic platforms, such as flying drones, where size or weight are limiting factors. In comparison to other recently proposed hardware solutions for bio-inspired processing of visual information on autonomous robots [47], the direct implementation of the processing unit on the robot avoids computational bottlenecks such as the transmission-related reduction of the frame rate. By employing behavioral strategies such as active head stabilization-which is also found in insects-it might be possible to further reduce the influence of rotational optic flow components which potentially obfuscate the estimation of relative nearness from optic flow [15].…”
Section: Plos Onementioning
confidence: 99%
“…Visual navigation is supported by path integration (Heinze et al, 2018) which runs in the background, providing a failsafe, and in some cases and situations, also by olfactory, tactile and magnetic cues (Buehlmann et al, 2012(Buehlmann et al, , 2015Knaden and Graham, 2016;Fleischmann et al, 2018). Evidence from behavioral studies and increasingly detailed knowledge of neural circuits relevant for navigation (e.g., Stone et al, 2017;Buehlmann et al, 2020;Kamhi et al, 2020;Steinbeck et al, 2020) are beginning to feed into neurally constrained and experimentally informed models of navigation (e.g., Baddeley et al, 2012;Ardin et al, 2016;Webb and Wystrach, 2016;Stone et al, 2017;Hoinville and Wehner, 2018;Gkanias et al, 2019;Schulte et al, 2019;Differt and Stürzl, 2020;Sun et al, 2020) and into robotic implementations (e.g., Lambrinos et al, 2000;Möller, 2000;Stone et al, 2016Stone et al, , 2017Webb and Wystrach, 2016;Sabo et al, 2017;Dupeyroux et al, 2018).…”
Section: Introductionmentioning
confidence: 99%