| 1. |
- Bregu, Endri, et al.
(författare)
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Reactive control of autonomous drones
- 2016
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Ingår i: MobiSys 2016 - Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services. - New York, NY, USA : Association for Computing Machinery, Inc. - 9781450342698 ; , s. 207-219
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Konferensbidrag (refereegranskat)abstract
- Aerial drones, ground robots, and aquatic rovers enable mobile applications that no other technology can realize with comparable flexibility and costs. In existing platforms, the low-level control enabling a drone's autonomous movement is currently realized in a time-triggered fashion, which simplifies implementations. In contrast, we conceive a notion of reactive control that supersedes the time-triggered approach by leveraging the characteristics of existing control logic and of the hardware it runs on. Using reactive control, control decisions are taken only upon recognizing the need to, based on observed changes in the navigation sensors. As a result, the rate of execution dynamically adapts to the circumstances. Compared to time-triggered control, this allows us to: i) attain more timely control decisions, ii) improve hardware utilization, iii) lessen the need to overprovision control rates. Based on 260+ hours of real-world experiments using three aerial drones, three different control logic, and three hardware platforms, we demonstrate, for example, up to 41% improvements in control accuracy and up to 22% improvements in flight time.
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| 2. |
- Mottola, Luca, et al.
(författare)
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Fundamental concepts of reactive control for autonomous drones
- 2018
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Ingår i: Communications of the ACM. - : Association for Computing Machinery (ACM). - 0001-0782 .- 1557-7317. ; 61:10, s. 96-104
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Tidskriftsartikel (refereegranskat)abstract
- Autonomous drones represent a new breed of mobile computing system. Compared to smartphones and connected cars that only opportunistically sense or communicate, drones allow motion control to become part of the application logic. The efficiency of their movements is largely dictated by the low-level control enabling their autonomous operation based on high-level inputs. Existing implementations of such low-level control operate in a timetriggered fashion. In contrast, we conceive a notion of reactive control that allows drones to execute the low-level control logic only upon recognizing the need to, based on the influence of the environment onto the drone operation. As a result, reactive control can dynamically adapt the control rate. This brings fundamental benefits, including more accurate motion control, extended lifetime, and better quality of service in end-user applications. Based on 260+ hours of real-world experiments using three aerial drones, three different control logic, and three hardware platforms, we demonstrate, for example, up to 41% improvements in motion accuracy and up to 22% improvements in flight time.
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| 3. |
- Mottola, Luca, et al.
(författare)
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Poster abstract : Towards spatial macroprogramming for sensing and actuating robot swarms
- 2013
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Ingår i: SenSys 2013 - Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems. - New York, NY, USA : Association for Computing Machinery. - 9781450320276
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Konferensbidrag (refereegranskat)abstract
- We present our ongoing work on the design of macropro- gramming abstractions to program sensing and actuating applications using robot swarms. Robots can sample the environment and act on it where no other sensor can reach, e.g., to monitor the environment at altitude with aerial robots. Programming the individual behavior of multiple coordinat- ing robots is dificult. We design LiftOff, a macropro- gramming abstraction that allows to program robot swarms collectively, by creating the illusion of a single computing device that occupies the entire physical space of interest. We achieve this by giving variables and values in a pro- gramming language a spatial semantics. In LiftOff, values may be associated to a location, and programmers use the same variable to access diferent values at diferent locations, sparing the need to manually create a mapping from variables to spatial values. LiftOff applications execute synchronously or based on lazy evaluation. The former allows precise program analysis, e.g., usng model checking, whilst the latter potentially executes faster. In this paper, we report on LiftOff's initial design and prototypes.
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