The Flight Assembled Architecture installation: Cooperative construction with flying machines

Augugliaro, Frederico; Lupashin, Sergei; Hamer, Michael; Male, Cason; Hehn, Markus; Mueller, Mark W.; Willmann, Jan; Gramazio, Fabio; Köhler, Matthias; D’Andrea, Raffaello

doi:10.1109/mcs.2014.2320359

Cited by 239 publications

(52 citation statements)

References 19 publications

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“…As a matter of fact, control electronics are getting less expensive, more powerful, and with smaller footprints, following trends predicted by Moore's law [81]. One would argue that the same holds also for light-weight sensors, 3 thus constantly driving the weight of an aerial vehicle down. Unfortunately, batteries do not follow Moore's law, and continue to account for 25-50% of the weight of small UAVs [18].…”

Section: Weight Reductionmentioning

confidence: 99%

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Energetics in robotic flight at small scales

Karydis

Kumar

2017

Interface Focus.

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Recent advances in design, sensing and control have led to aerial robots that offer great promise in a range of real-world applications. However, one critical open question centres on how to improve the energetic efficiency of aerial robots so that they can be useful in practical situations. This review paper provides a survey on small-scale aerial robots (i.e. less than 1 m 2 area foot print, and less than 3 kg weight) from the point of view of energetics. The paper discusses methods to improve the efficiency of aerial vehicles, and reports on recent findings by the authors and other groups on modelling the impact of aerodynamics for the purpose of building energy-aware motion planners and controllers.

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Section: Weight Reductionmentioning

confidence: 99%

“…2 For example, the Intel NUC mini PC: http://www.intel.com/content/www/us/en/nuc/nuc-kit-nuc5i7ryh.html. 3 Consider for instance recent developments in LiDARs, which are critical for mapping, localization and autonomous navigation and obstacle avoidance. 4 More about energy-aware trajectory generation follows in §3.…”

Section: Endnotesmentioning

confidence: 99%

Energetics in robotic flight at small scales

Karydis

Kumar

2017

Interface Focus.

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“…Of these, quadrotors have enjoyed the spotlight due to their high maneuverability, their ability to take-off vertically (as opposed to most fixed wing MAVs, for instance), and their relative simplicity in design (Gupte et al, 2012;Kumar and Michael, 2012). MAVs can be used for surveillance and mapping (Mohr and Fitzpatrick, 2008;Scaramuzza et al, 2014;Saska et al, 2016b), infrastructure inspection (Sa and Corke, 2014), load transport and delivery (Palunko et al, 2012), or construction (Lindsey et al, 2012;Augugliaro et al, 2014). Such applications are particularly useful in areas that are not easily accessible by humans, like forests or disaster sites (Alexis et al, 2009;Achtelik et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

A Survey on Swarming With Micro Air Vehicles: Fundamental Challenges and Constraints

et al. 2020

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This work presents a review and discussion of the challenges that must be solved in order to successfully develop swarms of Micro Air Vehicles (MAVs) for real world operations. From the discussion, we extract constraints and links that relate the local level MAV capabilities to the global operations of the swarm. These should be taken into account when designing swarm behaviors in order to maximize the utility of the group. At the lowest level, each MAV should operate safely. Robustness is often hailed as a pillar of swarm robotics, and a minimum level of local reliability is needed for it to propagate to the global level. An MAV must be capable of autonomous navigation within an environment with sufficient trustworthiness before the system can be scaled up. Once the operations of the single MAV are sufficiently secured for a task, the subsequent challenge is to allow the MAVs to sense one another within a neighborhood of interest. Relative localization of neighbors is a fundamental part of self-organizing robotic systems, enabling behaviors ranging from basic relative collision avoidance to higher level coordination. This ability, at times taken for granted, also must be sufficiently reliable. Moreover, herein lies a constraint: the design choice of the relative localization sensor has a direct link to the behaviors that the swarm can (and should) perform. Vision-based systems, for instance, force MAVs to fly within the field of view of their camera. Range or communication-based solutions, alternatively, provide omni-directional relative localization, yet can be victim to unobservable conditions under certain flight behaviors, such as parallel flight, and require constant relative excitation. At the swarm level, the final outcome is thus intrinsically influenced by the on-board abilities and sensors of the individual. The real-world behavior and operations of an MAV swarm intrinsically follow in a bottom-up fashion as a result of the local level limitations in cognition, relative knowledge, communication, power, and safety. Taking these local limitations into account when designing a global swarm behavior is key in order to take full advantage of the system, enabling local limitations to become true strengths of the swarm.

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“…Synchronization is ubiquitous in nature [1,2], man-made systems [3] and human behaviors [4]. Understanding synchronizing processes and regulating synchronizability have already benefited both biological and engineering systems [5], including foraging [6], predator avoidance [7], migration [8], collective control of unmanned air vehicles [9], and the self-organized formation of multi-robot systems [10]. Synchronization phenomena and such closely related concepts as collective motion and consensus have already attracted more and more attentions in many branches of science [11,12].…”

Section: Introductionmentioning

confidence: 99%

Ultrafast synchronization via local observation

Zhang

Fan

et al. 2019

New J. Phys.

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This paper proposes a Hankel matrix-based statistical study to calculate the final synchronization state of the entire network via local observation of just a single node for a time period significantly shorter than the synchronization process. It surfaces that synchronization can be achieved more quickly than the routine rhythm for networks no matter with linear or nonlinear dynamics. This finding refines our understanding of the abundant ultrafast synchronization phenomena observed in nature, which enables the efficient design of self-aligned robots as well.

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The Flight Assembled Architecture installation: Cooperative construction with flying machines

Cited by 239 publications

References 19 publications

Energetics in robotic flight at small scales

Energetics in robotic flight at small scales

A Survey on Swarming With Micro Air Vehicles: Fundamental Challenges and Constraints

Ultrafast synchronization via local observation

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