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Erschienen in: Autonomous Robots 4/2016

01.04.2016

Aerial robotic contact-based inspection: planning and control

verfasst von: Kostas Alexis, Georgios Darivianakis, Michael Burri, Roland Siegwart

Erschienen in: Autonomous Robots | Ausgabe 4/2016

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Abstract

The challenge of aerial robotic contact-based inspection is the driving motivation of this paper. The problem is approached on both levels of control and path-planning by introducing algorithms and control laws that ensure optimal inspection through contact and controlled aerial robotic physical interaction. Regarding the flight and physical interaction stabilization, a hybrid model predictive control framework is proposed, based on which a typical quadrotor becomes capable of stable and active interaction, accurate trajectory tracking on environmental surfaces as well as force control. Convex optimization techniques enabled the explicit computation of such a controller which accounts for the dynamics in free-flight as well as during physical interaction, ensures the global stability of the hybrid system and provides optimal responses while respecting the physical limitations of the vehicle. Further augmentation of this scheme, allowed the incorporation of a last-resort obstacle avoidance mechanism at the control level. Relying on such a control law, a contact-based inspection planner was developed which computes the optimal route within a given set of inspection points while avoiding any obstacles or other no-fly zones on the environmental surface. Extensive experimental studies that included complex “aerial-writing” tasks, interaction with non-planar and textured surfaces, execution of multiple inspection operations and obstacle avoidance maneuvers, indicate the efficiency of the proposed methods and the potential capabilities of aerial robotic inspection through contact.

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Fußnoten
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Metadaten
Titel
Aerial robotic contact-based inspection: planning and control
verfasst von
Kostas Alexis
Georgios Darivianakis
Michael Burri
Roland Siegwart
Publikationsdatum
01.04.2016
Verlag
Springer US
Erschienen in
Autonomous Robots / Ausgabe 4/2016
Print ISSN: 0929-5593
Elektronische ISSN: 1573-7527
DOI
https://doi.org/10.1007/s10514-015-9485-5

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