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Fabrizio Mura

dblp:87/5665 · DBLP profile ↗
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3ranked-venue papers
2as first author
0since 2021 · last 1998
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 3 · 2 first-authorSystems, architecture and hardware · 2 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
2 papers
Robot navigation and mapping · 64% Motion planning and robot control · 28% Video understanding and tracking · 8%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Motion planning and robot control
motion planning
0.011998
Visual Guidance of a Small Mobile Robot using Active, Biologically-Inspired, Eye Movements · ICRA 1998
Robotics › Robot navigation and mapping › mobile robot perception
visual sensing
0.011998
A Small-Sized Panoramic Scanning Visual Sensor Inspired by the Fly's Compound Eye · ICRA 1998
Computer vision › Video understanding and tracking
motion detection
0.011998
A Small-Sized Panoramic Scanning Visual Sensor Inspired by the Fly's Compound Eye · ICRA 1998
Robotics › Robot navigation and mapping
obstacle avoidance
0.011998
A Small-Sized Panoramic Scanning Visual Sensor Inspired by the Fly's Compound Eye · ICRA 1998

Methods — techniques the papers use, named apart from their topics

visually-guided eye rotations · 0.0pulsed retinal scanning · 0.0piezoelectric actuation · 0.0analog motion detection circuits · 0.0
YearPublicationVenuePosition
1998 A Small-Sized Panoramic Scanning Visual Sensor Inspired by the Fly's Compound Eye
abstract
We investigate the feasibility of the design of a small artificial compound eye that comprises micro-optical, micro-mechanical components and additional electronics for visual processing. The hybrid integration of this "mini-sensor" addresses important issues such as mechanic scale-effect, assembly of small parts and functional testing. The use of retinal scanning for the perception of visual motion is highlighted in the design of a small-sized horizontal array with a scanning retina of 2/spl times/30 photoreceptor elements (R/sub eye/=30 mm). The scanning motion is achieved by actuating the photodiode arrays with a piezoelectric bimorph cantilever beam coupled to a plate spring. The mini-compound eye, equipped with analogue motion detecting circuits, is able to guide the steps of a small mobile platform and perform multi-task visual processing for obstacle avoidance, tracking and pursuit of visual target.
Kazunori Hoshino, Fabrizio Mura, Hiroshi Morii, Keigo Suematsu, Isao Shimoyama
ICRA2
1998 Visual Guidance of a Small Mobile Robot using Active, Biologically-Inspired, Eye Movements
abstract
We introduce and implement a way of processing visual motion, which is directly inspired by the functional features of insects' visual systems. Rather than focusing on the computational performances of visual processing, alternative ways of detecting visual cues involving controlled eye movements are investigated. In this case, we show that the combination of retinal/eye movements significantly enhances the visual perception of motion for a sighted observer. The two kinds of eye movements introduced are: 1) pulsed retinal scanning, and 2) visually-guided eye rotations. Pulsed retinal scanning helps the eye to detect visual contrasts with enhanced reliability by increasing the S/N ratio of early visual signals. Rotations of the eye help a moving observer to maintain a continuous visual contact with obstacles while tracking their motion using pulses of retinal scanning. A direct demonstration of the performances has been implemented on a prototype eye, that successfully guides the motion of HECTOR, a small mobile platform, autonomously and in real-time.
Fabrizio Mura, Isao Shimoyama
ICRA1
1996 Biologically inspired eye movements for visually guided navigation of mobile robots
Fabrizio Mura, Nicolas H. Franceschini
ESANN1