Honeybee-based biohybrid system for landmine detection

This research was funded in part by NATO Science for Peace and Security (SPS) Programme, project number SPS 985355, “Biological Method (Bees) for Explosive Detection”.Legacy landmines in post-conflict areas are a non-discriminatory lethal hazard and can still be triggered decades after the conflict has ended. Efforts to detect these explosive devices are expensive, time-consuming, and dangerous to humans and animals involved. While methods such as metal detectors and sniffer dogs have successfully been used in humanitarian demining, more tools are required for both site surveying and accurate mine detection. Honeybees have emerged in recent years as efficient bioaccumulation and biomonitoring animals. The system reported here uses two complementary landmine detection methods: passive sampling and active search. Passive sampling aims to confirm the presence of explosive materials in a mine-suspected area by the analysis of explosive material brought back to the colony on honeybee bodies returning from foraging trips. Analysis is performed by light-emitting chemical sensors detecting explosives thermally desorbed from a preconcentrator strip. The active search is intended to be able to pinpoint the place where individual landmines are most likely to be present. Used together, both methods are anticipated to be useful in an end-to-end process for area surveying, suspected hazardous area reduction, and post-clearing internal and external quality control in humanitarian demining.Publisher PDFPeer reviewe

A computer vision approach to monitoring the activity and well-being of honeybees

Honeybees, in their role as pollinators, are vital to both agriculture and the wider ecosystem. However, they have experienced a serious decline across much of the world over recent years. Monitoring their well-being, and taking appropriate action if that is in jeopardy, has thus become a matter of great importance. In this paper, we present an approach based on computer vision to monitor bee activity and motion in the vicinity of an entrance/exit to a hive, including identifying and counting the number of bees approaching or leaving the hive in a given image frame or sequence of image frames

A bee in the corridor: centering and wall-following

International audienceIn an attempt to better understand the mechanism underlying lateral collision avoidance in 7 flying insects, we trained honeybees (Apis mellifera) to fly through a large (95cm-wide) flight 8 tunnel. We found that depending on the entrance and feeder positions, honeybees would 9 either center along the corridor midline or fly along one wall. Bees kept following one wall 10 even when a major (150cm-long) part of the opposite wall was removed. These findings 11 cannot be accounted for by the 'optic flow balance' hypothesis that has been put forward to 12 explain the typical bees' 'centering response' observed in narrower corridors. Both centering 13 and wall-following behaviours are well accounted for, however, by a mechanism called the 14 lateral optic flow regulator, i.e., a feedback system that strives to maintain the unilateral optic 15 flow constant. The power of this mechanism is that it would allow the bee to guide itself 16 visually in a corridor without having to measure its speed or distance from the walls

Optic Flow Based Autopilots: Speed Control and Obstacle Avoidance

International audienceThe explicit control schemes presented here explain how insects may navigate on the sole basis of optic flow (OF) cues without requiring any distance or speed measurements: how they take off and land, follow the terrain, avoid the lateral walls in a corridor and control their forward speed automatically. The optic flow regulator, a feedback system controlling either the lift, the forward thrust or the lateral thrust, is described. Three OF regulators account for various insect flight patterns observed over the ground and over still water, under calm and windy conditions and in straight and tapered corridors. These control schemes were simulated experimentally and/or implemented onboard two types of aerial robots, a micro helicopter (MH) and a hovercraft (HO), which behaved much like insects when placed in similar environments. These robots were equipped with opto-electronic OF sensors inspired by our electrophysiological findings on houseflies' motion sensitive visual neurons. The simple, parsimonious control schemes described here require no conventional avionic devices such as range finders, groundspeed sensors or GPS receivers. They are consistent with the the neural repertoire of flying insects and meet the low avionic payload requirements of autonomous micro aerial and space vehicles

Insect inspired behaviours for the autonomous control of mobile robots

Animals navigate through various uncontrolled environments with seemingly little effort. Flying insects, especially, are quite adept at manoeuvring in complex, unpredictable and possibly hostile environments. Through both simulation and real-world experiments, we demonstrate the feasibility of equipping a mobile robot with the ability to navigate a corridor environment, in real time, using principles based on insect-based visual guidance. In particular we have used the bees&rsquo; navigational strategy of measuring object range in terms of image velocity. We have also shown the viability and usefulness of various other insect behaviours: (i) keeping walls equidistant, (ii) slowing down when approaching an object, (iii) regulating speed according to tunnel width, and (iv) using visual motion as a measure of distance travelled.<br /

Bumblebee foraging rhythms under the midnight sun measured with radiofrequency identification

<p>Abstract</p> <p>Background</p> <p>In the permanent daylight conditions north of the Arctic circle, there is a unique opportunity for bumblebee foragers to maximise intake, and therefore colony growth, by remaining active during the entire available 24-h period. We tested the foraging rhythms of bumblebee (<it>Bombus terrestris </it>and <it>B. pascuorum</it>) colonies in northern Finland during the summer, when the sun stays above the horizon for weeks. We used fully automatic radio-frequency identification to monitor the foraging activity of more than 1,000 workers and analysed their circadian foraging rhythms.</p> <p>Results</p> <p>Foragers did not use the available 24-h foraging period but exhibited robust diurnal rhythms instead. A mean of 95.2% of the tested <it>B. terrestris </it>workers showed robust diurnal rhythms with a mean period of 23.8 h. Foraging activity took place mainly between 08:00 and 23:00, with only low or almost no activity during the rest of the day. Activity levels increased steadily during the morning, reached a maximum around midday and decreased again during late afternoon and early evening. Foraging patterns of native <it>B. pascuorum </it>followed the same temporal organisation, with the foraging activity being restricted to the period between 06:00 and 22:00.</p> <p>Conclusions</p> <p>The results of the present study indicate that the circadian clock of the foragers must have been entrained by some external cue, the most prominent being daily cycles in light intensity and temperature. Daily fluctuations in the spectral composition of light, especially in the UV range, could also be responsible for synchronising the circadian clock of the foragers under continuous daylight conditions.</p

Neuromimetic Robots inspired by Insect Vision

International audienceEquipped with a less-than-one-milligram brain, insects fly autonomously in complex environments without resorting to any Radars, Ladars, Sonars or GPS. The knowledge gained during the last decades on insects' sensory-motor abilities and the neuronal substrates involved provides us with a rich source of inspiration for designing tomorrow's self-guided vehicles and micro-vehicles, which are to cope with unforeseen events on the ground, in the air, under water or in space. Insects have been in the business of sensory-motor integration for several 100 millions years and can therefore teach us useful tricks for designing agile autonomous vehicles at various scales. Constructing a "biorobot" first requires exactly formulating the signal processing principles at work in the animal. It gives us, in return, a unique opportunity of checking the soundness and robustness of those principles by bringing them face to face with the real physical world. Here we describe some of the visually-guided terrestrial and aerial robots we have developed on the basis of our biological findings. These robots (Robot Fly, SCANIA, FANIA, OSCAR, OCTAVE and LORA) all react to the optic flow (i.e., the angular speed of the retinal image). Optic flow is sensed onboard the robots by miniature vision sensors called Elementary Motion Detectors (EMDs). The principle of these electro-optical velocity sensors was derived from optical/electrophysiological studies where we recorded the responses of single neurons to optical microstimulation of single photoreceptor cells in a model visual system: the fly's compound eye. Optic flow based sensors rely solely on contrast provided by reflected (or scattered) sunlight from any kind of celestial bodies in a given spectral range. These nonemissive, powerlean sensors offer potential applications to manned or unmanned aircraft. Applications can also be envisaged to spacecraft, from robotic landers and rovers to asteroid explorers or space station dockers, with interesting prospects as regards reduction in weight and consumption