Optic flow-based vision system for autonomous 3D localization and control of small aerial vehicles

Kendoul, Farid; Fantoni, Isabelle; Nonami, Kenzo

doi:10.1016/j.robot.2009.02.001

Cited by 228 publications

(106 citation statements)

References 30 publications

Supporting

Mentioning

106

Contrasting

Order By: Relevance

“…Furthermore, both simultaneous localization and mapping and altitude control have been demonstrated in quadcopters with two sets of stereo cameras, one set pointing forwards and one set pointing downwards 89 . Simultaneous localization and mapping algorithms have also been combined with optic flow methods to estimate distances from the surrounding environment and stabilize the drone 90 .…”

Section: Cognitive Autonomymentioning

confidence: 99%

Science, technology and the future of small autonomous drones

Floreano

Wood

2015

Nature

1,087

552

View full text Add to dashboard Cite

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...

show abstract

Section: Cognitive Autonomymentioning

confidence: 99%

Science, technology and the future of small autonomous drones

Floreano

Wood

2015

Nature

1,087

552

View full text Add to dashboard Cite

show abstract

“…In order to localize, we must have both the magnetic field strength and a position estimation of the UAV. However, since GPS error is too high, we use an optical flow camera, which can provide accurate motion estimates over short periods of time [21,22] with higher accuracy than GPS.…”

Section: Localizationmentioning

confidence: 99%

“…The particular optical flow camera we attempted to use in our system (PX4Flow [21]) was very sensitive to its viewing surface. We tested many surfaces and found a minimum error of 0.2 m over a 10 s flight over a textured wood surface (similar to that reported by the developers), but very poor results with other materials.…”

Section: Localizationmentioning

confidence: 99%

Experimental Analysis of a UAV-Based Wireless Power Transfer Localization System

Mittleider

Griffin

Detweiler

2015

Experimental Robotics

View full text Add to dashboard Cite

Abstract. Sensors deployed in remote locations provide unprecedented amounts of data, but powering these sensors over long periods remains a challenge. In this paper, we develop and present a UAV-based wireless power transfer system. We discuss design considerations and present our system that allows a UAV to fly to remote locations to charge hard to access sensors. We analyze the impact of different materials on the wireless power transfer system. Since GPS does not provide sufficient accuracy, we develop and experimentally characterize a relative localization algorithm based on sensing the magnetic field of the power transfer system and optical flow that allows the UAV to localize the sensor with an average error of 15 cm to enable the transfer of on average 4.2 W . These results overcome some of the practical challenges associated with wirelessly charging sensors with a UAV and show that UAVs with wireless power transfer systems can greatly extend the life of remotely deployed sensors.

show abstract

“…The latter experiments were ran in environments that consists of large flat walls, because small obstacles cannot be distinguished from the few measurement points that these sensors provide. Optic-flow, coupled with other sensor modalities, is a popular approach to extract the distance to the surrounding obstacles such as in [1], [22], [23], [24]. However, the optic-flow approaches presented here all rely on external systems or external processing to operate and illustrate the complexity of extracting distances from optic-flow.…”

Section: Sensors and Control For Robots That Can Recover From Comentioning

confidence: 99%

The AirBurr: A flying robot that can exploit collisions

Briod

Klaptocz

Zufferey

et al. 2012

2012 ICME International Conference on Complex Medical Engineering (CME)

View full text Add to dashboard Cite

Abstract-Research made over the past decade shows the use of increasingly complex methods and heavy platforms to achieve autonomous flight in cluttered environments. However, efficient behaviors can be found in nature where limited sensing is used, such as in insects progressing toward a light at night. Interestingly, their success is based on their ability to recover from the numerous collisions happening along their imperfect flight path. The goal of the AirBurr project is to take inspiration from these insects and develop a new class of flying robots that can recover from collisions and even exploit them. Such robots are designed to be robust to crashes and can take-off again without human intervention. They navigate in a reactive way, bump into obstacles, and unlike conventional approaches, they don't need heavy modeling in order to fly autonomously. We believe that this new paradigm will bring flying robots out of the laboratory and allow them to tackle unstructured, cluttered environments.This paper aims at presenting the vision of the AirBurr project, as well as the latest results in the design of a platform capable of sustaining collisions and self-recovering after crashes.Index Terms-Robust bio-inspired indoor flying robot.

show abstract

Optic flow-based vision system for autonomous 3D localization and control of small aerial vehicles

Cited by 228 publications

References 30 publications

Science, technology and the future of small autonomous drones

Science, technology and the future of small autonomous drones

Experimental Analysis of a UAV-Based Wireless Power Transfer Localization System

The AirBurr: A flying robot that can exploit collisions

Contact Info

Product

Resources

About