NDLI: Energy-efficient indoor search by swarms of simulated flying robots without global information

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Energy-efficient indoor search by swarms of simulated flying robots without global information

Content Provider	Springer Nature Link
Author	Stirling, Timothy Wischmann, Steffen Florea, Dario
Copyright Year	2010
Abstract	Swarms of flying robots are a promising alternative to ground-based robots for search in indoor environments with advantages such as increased speed and the ability to fly above obstacles. However, there are numerous problems that must be surmounted including limitations in available sensory and on-board processing capabilities, and low flight endurance. This paper introduces a novel strategy to coordinate a swarm of flying robots for indoor exploration that significantly increases energy efficiency. The presented algorithm is fully distributed and scalable. It relies solely on local sensing and low-bandwidth communication, and does not require absolute positioning, localisation, or explicit world-models. It assumes that flying robots can temporarily attach to the ceiling, or land on the ground for efficient surveillance over extended periods of time. To further reduce energy consumption, the swarm is incrementally deployed by launching one robot at a time. Extensive simulation experiments demonstrate that increasing the time between consecutive robot launches significantly lowers energy consumption by reducing total swarm flight time, while also decreasing collision probability. As a trade-off, however, the search time increases with increased inter-launch periods. These effects are stronger in more complex environments. The proposed localisation-free strategy provides an energy efficient search behaviour adaptable to different environments or timing constraints.
Starting Page	117
Ending Page	143
Page Count	27
File Format	PDF
ISSN	19353812
Journal	Swarm Intelligence
Volume Number	4
Issue Number	2
e-ISSN	19353820
Language	English
Publisher	Springer US
Publisher Date	2010-02-17
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Flying robots Swarm search Localisation-free search Energy-efficiency Mobile robot sensor network deployment Computer Communication Networks Communications Engineering, Networks ApplicationMathematics/Computational Methods of Engineering Computer Systems Organization and Communication Networks Artificial Intelligence (incl. Robotics)
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence

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