Sparse Robot Swarms: Moving Swarms to Real-World Applications
Robot swarms are groups of robots that each act autonomously based on only local perception and coordination with neighboring robots. While current swarm implementations can be large in size (e.g., 1,000 robots), they are typically constrained to working in highly controlled indoor environments. Mor...
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doaj-1573f0feb2894697bd636cb8b2d7eff22020-11-25T03:13:25ZengFrontiers Media S.A.Frontiers in Robotics and AI2296-91442020-07-01710.3389/frobt.2020.00083521822Sparse Robot Swarms: Moving Swarms to Real-World ApplicationsDanesh Tarapore0Roderich Groß1Klaus-Peter Zauner2School of Electronics and Computer Science, University of Southampton, Southampton, United KingdomDepartment of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, United KingdomSchool of Electronics and Computer Science, University of Southampton, Southampton, United KingdomRobot swarms are groups of robots that each act autonomously based on only local perception and coordination with neighboring robots. While current swarm implementations can be large in size (e.g., 1,000 robots), they are typically constrained to working in highly controlled indoor environments. Moreover, a common property of swarms is the underlying assumption that the robots act in close proximity of each other (e.g., 10 body lengths apart), and typically employ uninterrupted, situated, close-range communication for coordination. Many real world applications, including environmental monitoring and precision agriculture, however, require scalable groups of robots to act jointly over large distances (e.g., 1,000 body lengths), rendering the use of dense swarms impractical. Using a dense swarm for such applications would be invasive to the environment and unrealistic in terms of mission deployment, maintenance and post-mission recovery. To address this problem, we propose the sparse swarm concept, and illustrate its use in the context of four application scenarios. For one scenario, which requires a group of rovers to traverse, and monitor, a forest environment, we identify the challenges involved at all levels in developing a sparse swarm—from the hardware platform to communication-constrained coordination algorithms—and discuss potential solutions. We outline open questions of theoretical and practical nature, which we hope will bring the concept of sparse swarms to fruition.https://www.frontiersin.org/article/10.3389/frobt.2020.00083/fullswarm roboticsmultirobot systemsfield roboticsforest robotssparse couplingcommunication networks |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Danesh Tarapore Roderich Groß Klaus-Peter Zauner |
spellingShingle |
Danesh Tarapore Roderich Groß Klaus-Peter Zauner Sparse Robot Swarms: Moving Swarms to Real-World Applications Frontiers in Robotics and AI swarm robotics multirobot systems field robotics forest robots sparse coupling communication networks |
author_facet |
Danesh Tarapore Roderich Groß Klaus-Peter Zauner |
author_sort |
Danesh Tarapore |
title |
Sparse Robot Swarms: Moving Swarms to Real-World Applications |
title_short |
Sparse Robot Swarms: Moving Swarms to Real-World Applications |
title_full |
Sparse Robot Swarms: Moving Swarms to Real-World Applications |
title_fullStr |
Sparse Robot Swarms: Moving Swarms to Real-World Applications |
title_full_unstemmed |
Sparse Robot Swarms: Moving Swarms to Real-World Applications |
title_sort |
sparse robot swarms: moving swarms to real-world applications |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Robotics and AI |
issn |
2296-9144 |
publishDate |
2020-07-01 |
description |
Robot swarms are groups of robots that each act autonomously based on only local perception and coordination with neighboring robots. While current swarm implementations can be large in size (e.g., 1,000 robots), they are typically constrained to working in highly controlled indoor environments. Moreover, a common property of swarms is the underlying assumption that the robots act in close proximity of each other (e.g., 10 body lengths apart), and typically employ uninterrupted, situated, close-range communication for coordination. Many real world applications, including environmental monitoring and precision agriculture, however, require scalable groups of robots to act jointly over large distances (e.g., 1,000 body lengths), rendering the use of dense swarms impractical. Using a dense swarm for such applications would be invasive to the environment and unrealistic in terms of mission deployment, maintenance and post-mission recovery. To address this problem, we propose the sparse swarm concept, and illustrate its use in the context of four application scenarios. For one scenario, which requires a group of rovers to traverse, and monitor, a forest environment, we identify the challenges involved at all levels in developing a sparse swarm—from the hardware platform to communication-constrained coordination algorithms—and discuss potential solutions. We outline open questions of theoretical and practical nature, which we hope will bring the concept of sparse swarms to fruition. |
topic |
swarm robotics multirobot systems field robotics forest robots sparse coupling communication networks |
url |
https://www.frontiersin.org/article/10.3389/frobt.2020.00083/full |
work_keys_str_mv |
AT daneshtarapore sparserobotswarmsmovingswarmstorealworldapplications AT roderichgroß sparserobotswarmsmovingswarmstorealworldapplications AT klauspeterzauner sparserobotswarmsmovingswarmstorealworldapplications |
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1724646859689951232 |