Vision-Controlled Micro Flying Robots: From System Design to Autonomous Navigation and Mapping in GPS-Denied Environments

Scaramuzza, Davide; Achtelik, Michael; Doitsidis, Lefteris; Fraundorfer, Friedrich; Kosmatopoulos, Elias B.; Martinelli, Agostino; Achtelik, Markus; Chli, Margarita; Chatzichristofis, Savvas A.; Kneip, Laurent; Gurdan, Daniel; Heng, Lionel; Lee, Gim Hee; Lynen, Simon; Meier, Lorenz; Pollefeys, Marc; Renzaglia, Alessandro; Siegwart, Roland; Stumpf, Jan; Tanskanen, Petri; Troiani, Chiara; Weiß, Stephan

doi:10.1109/mra.2014.2322295

Cited by 267 publications

(169 citation statements)

References 52 publications

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“…This involves leveraging decades of research in statistical methods for vision-based navigation of terrestrial vehicles, such as visual odometry 82,83 and simultaneous localization and mapping 84 . For example, monocular vision has been successfully used for simultaneous localization and mapping of quadcopters in indoor 85 and outdoor environments 86 . However, these drones could not avoid obstacles that had not been previously detected and mapped.…”

Section: Cognitive Autonomymentioning

confidence: 99%

Science, technology and the future of small autonomous drones

Floreano

Wood

2015

Nature

1,087

552

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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: Cognitive Autonomymentioning

confidence: 99%

Science, technology and the future of small autonomous drones

Floreano

Wood

2015

Nature

1,087

552

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“…Although inertial navigation systems are unaffected by being underwater, they are costly and subject to drift [5]. Optical vision systems have been effectively used for navigation on land [6], in air [7] and underwater [8]. Underwater, they have the advantage in providing an absolute position referenced to the seabed.…”

Section: Introductionmentioning

confidence: 99%

Attitude-Trajectory Estimation for Forward-Looking Multibeam Sonar Based on Acoustic Image Registration

Henson

Zakharov

2019

IEEE J. Oceanic Eng.

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“…In light of the very considerable amount of research reported in ER over the last 25 years, and the lack of any fully evolved autonomous robotic system that might approach the state-ofthe-art performance of autonomous systems in general [81][82][83], it is likely that some methodological aspirations of ER are not feasible using current or near future technology. This paper has presented several arguments suggesting that direct goaldriven evolution of very complex autonomous robot behaviors, although possible in some specific cases, is not tractable in the general case.…”

Section: Resultsmentioning

confidence: 99%

Embodied artificial life at an impasse can evolutionary robotics methods be scaled?

Nelson¹

2014

2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS)

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Abstract-Evolutionary robotics (ER) investigates the application of artificial evolution toward the synthesis of robots capable of performing autonomous behaviors. Over the last 25 years, researchers have reported increasingly complex evolved behaviors, and have compiled a de facto set of benchmark tasks. Perhaps the best known of these is the obstacle avoidance and target homing task performed by differential drive robots. More complex tasks studied in recent ER work include augmented variants of the rodent T-maze and complex foraging tasks. But can proof-of-concept results such as these be extended to evolve complex autonomous behaviors in a general sense? In this topical analysis paper we survey relevant research and make the case that common tasks used to demonstrate the effectiveness of evolutionary robotics are not characteristic of more general cases and in fact do not fully prove the concept that artificial evolution can be used to evolve sophisticated autonomous agent behaviors. Robots capable of performing many of the tasks studied in ER have now been evolved using nearly aggregate binary success/fail fitness functions. However, arguments used to support the necessity of incremental methods for complex tasks are essentially sound. This raises the possibility that the tasks themselves allow for relatively simple solutions, or span a relatively small candidate solution set. This paper presents these arguments in detail and concludes with a discussion of current ER research.

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Vision-Controlled Micro Flying Robots: From System Design to Autonomous Navigation and Mapping in GPS-Denied Environments

Cited by 267 publications

References 52 publications

Science, technology and the future of small autonomous drones

Science, technology and the future of small autonomous drones

Attitude-Trajectory Estimation for Forward-Looking Multibeam Sonar Based on Acoustic Image Registration

Embodied artificial life at an impasse can evolutionary robotics methods be scaled?

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