Landing Strategies in Honeybees and Applications to Uninhabited Airborne Vehicles

Chahl, Javaan; Srinivasan, Mandyam V.; Zhang, Shao Wu

doi:10.1177/0278364904041320

Cited by 112 publications

(62 citation statements)

References 16 publications

(20 reference statements)

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“…For example, it has been shown that small fixed-wing drones 53 and helicopters 54 can regulate their distance from the ground using ventral optic flow while a GPS was used to maintain constant speed and an IMU was used to regulate roll angle. The addition of lateral optic flow sensors also allowed a fixed-wing drone to detect near-ground obstacles 55 .…”

Section: Review Insightmentioning

confidence: 99%

“…These methods consist of continuously adjusting flight speed and altitude to maintain constant optic flow signals, which has also been suggested by biological models 60 . For example, altitude control and landing was achieved by adding negative feedback from ventral optic flow, either to the control surfaces that regulate pitch angle 53 or to those that regulate thrust 61 . The latter method has also been shown to be effective for altitude control and landing on mobile platforms 62 and, when used in conjunction with lateral optic flow and lateral thrust, also for replicating flight trajectories of honeybees during indoor flight 62 .…”

Section: Review Insightmentioning

confidence: 99%

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Science, technology and the future of small autonomous drones

Floreano

Wood

2015

Nature

987

503

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Drones, a popular nickname for unmanned aerial vehicles and micro aerial vehicles, often conjure up images of unmanned aeroplanes that fly thousands of miles for espionage and to deploy munitions. However, over the past few years, an increasing number of public and private research laboratories have been working on small, human-friendly drones that one day may autonomously fly in confined spaces and in close proximity to people. The development of these small drones, which is the main focus of this Review, has been supported by the miniaturization and cost reduction of electronic components (microprocessors, sensors, batteries and wireless communication units), largely driven by the portable electronic device industry. These improvements have enabled the prototyping and commercialization of small (typically less than 1 kg) drones at smartphone prices.Small drones will have important socio-economic impacts (Fig. 1). Images from drones that are capable of flying a few metres above the ground will fill a gap between expensive, weather-dependent and lowresolution images provided by satellites and car-based images limited to human-level perspectives and the availability of accessible roads. Specialized flying cameras and cloud-based data analytics will allow farmers to continuously monitor the quality of crop growth. Such platforms will enable construction companies to measure work progress in real time. Drones will let mining companies obtain precise volumetric data of excavations. Energy and infrastructure companies will be able to exhaustively survey pipelines, roads and cables. Humanitarian organizations could immediately assess and adapt aid efforts in continuously changing refugee camps. Transportation drones that are capable of safely taking off and landing in the proximity of buildings and humans will allow developing countries -without a suitable road network -to rapidly deliver goods and to finally unleash the full potential of their e-commerce telecommunication infrastructure. Transportation drones will also help developed countries to improve the quality of service in congested or remote areas, and will enable rescue organizations to quickly deliver medical supplies in the field and on demand. Inspection drones that are capable of flying in confined spaces will help fire-fighting and emergency units to assess dangers faster and more safely, logistic companies to detect cracks in the inner and outer shells of ships, road maintenance companies to measure signs of wear and tear in bridges and tunnels, security companies to improve building safety by monitoring areas outside the range of surveillance cameras, and disaster mitigation agencies to inspect partially collapsed buildings where ground clutter is an obstacle for terrestrial robots. Coordinated teams of autonomous drones will enable missions that last longer than the flight time of a single drone by allowing some drones to temporarily leave the team for battery replacement. Drone teams will permit rescue organizations to quickly deploy dedicated commu...

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Section: Review Insightmentioning

confidence: 99%

Section: Review Insightmentioning

confidence: 99%

Science, technology and the future of small autonomous drones

Floreano

Wood

2015

Nature

987

503

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“…These behaviors originated in research on insect flight are appropriate for implementation in a biomimetic autopilot for small UAVs and robotics in general [17,18,19]. Potential applications of optical flow for small aerial vehicles include altitude control and terrain following [20,21], autonomous landing [20,22,23] and obstacles avoidance [24,25,26].…”

Section: Bio-inspired Vision-based Aerial Navigationmentioning

confidence: 99%

Optic Flow‐Based Vision System for Autonomous 3D Localization and Control of Small Aerial Vehicles

Kendoul

Fantoni²,

Nonami

2013

Unmanned Aerial Vehicles

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“…However those systems still required GPS and/or an IMU for the control. Other approaches have included optic flow in the control of flying platforms (Barrows et al 2001, Green et al 2003, Chahl et al 2004, but for regulating exclusively altitude or lateral steering and thus still requiring partial manual control. Optic flow has also been used for the control of indoor systems where GPS is not available and weight constraints are even stronger (Zufferey et Fig.…”

Section: State Of the Artmentioning

confidence: 99%

Vision-based control of near-obstacle flight

2009

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This paper presents a novel control strategy, which we call optiPilot, for autonomous flight in the vicinity of obstacles. Most existing autopilots rely on a complete 6-degree-of-freedom state estimation using a GPS and an Inertial Measurement Unit (IMU) and are unable to detect and avoid obstacles. This is a limitation for missions such as surveillance and environment monitoring that may require near-obstacle flight in urban areas or mountainous environments. OptiPilot instead uses optic flow to estimate proximity of obstacles and avoid them.Our approach takes advantage of the fact that, for most platforms in translational flight (as opposed to near-hover flight), the translatory motion is essentially aligned with the aircraft main axis. This property allows us to directly interpret optic flow measurements as proximity indications. We take inspiration from neural and behavioural strategies of flying insects to propose a simple mapping of optic flow measurements into control signals that requires only a lightweight and power-efficient sensor suite and minimal processing power.In this paper, we first describe results obtained in simulation before presenting the implementation of optiPilot on a real flying platform equipped only with lightweight and inexpensive optic computer mouse sensors, MEMS rate gyroscopes and a pressure-based airspeed sensor. We show that the proposed control strategy not only allows collision-free flight in the vicinity of obstacles, but is also able to stabilise both attitude and altitude over flat terrain. These re-

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Landing Strategies in Honeybees and Applications to Uninhabited Airborne Vehicles

Cited by 112 publications

References 16 publications

Science, technology and the future of small autonomous drones

Science, technology and the future of small autonomous drones

Optic Flow‐Based Vision System for Autonomous 3D Localization and Control of Small Aerial Vehicles

Vision-based control of near-obstacle flight

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