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DrunkWalk: Collaborative and Adaptive Planning for Navigation of Micro-Aerial Sensor Swarms

Authors:

Carlos Ruiz Dominguez,

Stefano Carpin,

Pei ZhangAuthors Info & Claims

SenSys '15: Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems

Pages 295 - 308

https://doi.org/10.1145/2809695.2809724

Published: 01 November 2015 Publication History

Abstract

Micro-aerial vehicle (MAV) swarms are a new class of mobile sensor networks with many applications, including search and rescue, urban surveillance, radiation monitoring, etc. These sensing applications require autonomously navigating a high number of low-cost, low-complexity MAV sensor nodes in hazardous environments. The lack of preexisting localization infrastructure and the limited sensing, computing, and communication abilities of individual nodes makes it challenging for nodes to autonomously navigate to suitable preassigned locations. In this paper, we present a collaborative and adaptive algorithm for resource-constrained MAV nodes to quickly and efficiently navigate to preassigned locations. Using radio fingerprints between flying and landed MAVs acting as radio beacons, the algorithm detects intersections in trajectories of mobile nodes. The algorithm combines noisy dead-reckoning measurements from multiple MAVs at detected intersections to improve the accuracy of the MAVs' location estimations. In addition, the algorithm plans intersecting trajectories of MAV nodes to aid the location estimation and provide desired performance in terms of timeliness and accuracy of navigation. We evaluate the performance of our algorithm through a real testbed implementation and large-scale physical feature based simulations. Our results show that, compared to existing autonomous navigation strategies, our algorithm achieves up to 6X reduction in location estimation errors, and as much as 3X improvement in navigation success rate under the given time and accuracy constraints.

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Index Terms

DrunkWalk: Collaborative and Adaptive Planning for Navigation of Micro-Aerial Sensor Swarms
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Multi-agent systems
2. Software and its engineering
  1. Software organization and properties
    1. Software system structures
      1. Distributed systems organizing principles
        Organizing principles for web applications

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cover image ACM Conferences

SenSys '15: Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems

November 2015

526 pages

ISBN:9781450336314

DOI:10.1145/2809695

General Chair:
Junehwa Song
KAIST, South Korea
,
Program Chairs:
Tarek Abdelzaher
University of Illinois at Urbana-Champaign, USA
,
Cecilia Mascolo
University of Cambridge, UK

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 01 November 2015

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SenSys '15

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SenSys '15: The 13th ACM Conference on Embedded Network Sensor Systems

November 1 - 4, 2015

Seoul, South Korea

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SenSys '15 Paper Acceptance Rate 27 of 132 submissions, 20%;

Overall Acceptance Rate 174 of 867 submissions, 20%

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SenSys '24

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Cited By

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https://dl.acm.org/doi/10.1145/3678549
Xu YDang FLiu KZhu ZChen XWang XMiao XZhao H(2024)BEANet: An Energy-efficient BLE Solution for High-capacity Equipment Area NetworkACM Transactions on Sensor Networks10.1145/364128020:3(1-23)Online publication date: 17-Jan-2024
https://dl.acm.org/doi/10.1145/3641280
Jian ZLiu ZShao HWang XChen XLiang B(2024)Path Generation for Wheeled Robots Autonomous Navigation on Vegetated TerrainIEEE Robotics and Automation Letters10.1109/LRA.2023.33341429:2(1764-1771)Online publication date: Feb-2024
https://doi.org/10.1109/LRA.2023.3334142
Chen XWang HCheng YFu HLiu YDang FLiu YCui JChen X(2024)DDL: Empowering Delivery Drones With Large-Scale Urban Sensing CapabilityIEEE Journal of Selected Topics in Signal Processing10.1109/JSTSP.2024.342737118:3(502-515)Online publication date: Apr-2024
https://doi.org/10.1109/JSTSP.2024.3427371
Zhao CRuan CWang SZha JWang HLi JLiu YWang XChen X(2024)Demo Abstract: Bio-inspired Tactile Sensing for MAV Landing with Extreme Low-cost Sensors2024 23rd ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)10.1109/IPSN61024.2024.00031(261-262)Online publication date: 13-May-2024
https://doi.org/10.1109/IPSN61024.2024.00031
Liu YJian ZTan JLiang LLiu HChen X(2024)Demo Abstract: Range-SLAM: UWB based Realtime Indoor Location and Mapping2024 23rd ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN)10.1109/IPSN61024.2024.00030(259-260)Online publication date: 13-May-2024
https://doi.org/10.1109/IPSN61024.2024.00030
Wang HXu JZhao CLu ZCheng YChen XZhang XLiu YChen X(2024)TransformLoc: Transforming MAVs into Mobile Localization Infrastructures in Heterogeneous SwarmsIEEE INFOCOM 2024 - IEEE Conference on Computer Communications10.1109/INFOCOM52122.2024.10621375(1101-1110)Online publication date: 20-May-2024
https://doi.org/10.1109/INFOCOM52122.2024.10621375
Zhang TJin XBai SPeng YLi YZhang J(2023)Smart Public Transportation Sensing: Enhancing Perception and Data Management for Efficient and Safety OperationsSensors10.3390/s2322922823:22(9228)Online publication date: 16-Nov-2023
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Luo JHu YYu CHong CZhang XChen X(2023)Field Reconstruction-Based Non-Rendezvous Calibration for Low Cost Mobile SensorsAdjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing10.1145/3594739.3612908(688-693)Online publication date: 8-Oct-2023
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