Signal Strength Coordination for Cooperative Mapping
01 Jan 2005-
TL;DR: This work proposes a multi-robot coordination method based on perceived wireless signal strength between cooperating robots for exploration in maze-like environments that is tested and compared to an existing method that relies on preserving a clear line of sight between robots to maintain communication.
Abstract: : This work addresses the problem of coordinating a team of mobile robots such that they form a connected ad-hoc wireless network while addressing task objectives. Many tasks, such as exploration or foraging, can be performed more efficiently when robots are able to communicate with each other. All or parts of these tasks can be performed in parallel, thus multiple robots can complete the task more quickly than a single robot. Communication and coordination among the robots can prevent robots from duplicating the effort of other robots, allowing the team to address the task more efficiently. In non-trivial environments, maintaining communication can be difficult due to the unpredictable nature of wireless signal propagation. We propose a multi-robot coordination method based on perceived wireless signal strength between cooperating robots for exploration in maze-like environments. This new method is tested and compared to an existing method that relies on preserving a clear line of sight between robots to maintain communication.
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TL;DR: A nominal model of an urban environment obtained by aerial surveillance, is used to generate strategies for exploration and the construction of a radio signal strength map is presented that can be used to plan multi‐robot tasks, and also serve as useful perceptual information.
Abstract: In this paper, we present an experimental study of strategies for maintaining end-to-end communication links for tasks such as surveillance, reconnaissance, and target search and identification, where team connectivity is required for situational awareness. Our main contributions are threefold: (a) We present the construction of a radio signal strength map that can be used to plan multi-robot tasks, and also serve as useful perceptual information. We show how a nominal model of an urban environment obtained by aerial surveillance, is used to generate strategies for exploration. (b) We present reactive controllers for communication link maintenance; and (c) we consider the differences between monitoring signal strength versus data throughput. Experimental results, obtained using our multi-robot testbed in three representative urban environments are presented with each of our main contributions. © 2008 Wiley Periodicals, Inc.
166 citations
Cites methods from "Signal Strength Coordination for Co..."
...…coordination strategies that rely on line-of-sight maintenance may significantly improve each agent’s ability to communicate, it has been shown through simulation by [Thibodeau et al., 2004], that line-of-sight maintenance strategies are often not necessary and may potentially be too restrictive....
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...Experimental results, obtained using our multi-robot testbed in three representative urban environments, are presented with each of our main contributions....
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TL;DR: This is a preprint of an article accepted for publication in the Journal of Field Robotics, copyright 2007 and will be published online in Wiley InterScience.
Abstract: This is a preprint of an article accepted for publication in the Journal of Field Robotics, copyright 2007.
Journal of Field Robotics 24(11), 991–1014 (2007) © 2007 Wiley Periodicals, Inc. Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/rob.202222
158 citations
Cites background from "Signal Strength Coordination for Co..."
...Tasks like searching or mapping [Thibodeau et al., 2004] can be achieved by deploying multiple robots performing operations in parallel in a coordinated fashion....
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26 May 2015
TL;DR: A multi-robot exploration algorithm that uses adaptive coordination to provide heterogeneous behavior to maximize the efficiency of exploring and mapping an unknown environment when a team is faced with unreliable communication and limited battery life is proposed.
Abstract: We propose a multi-robot exploration algorithm that uses adaptive coordination to provide heterogeneous behavior. The key idea is to maximize the efficiency of exploring and mapping an unknown environment when a team is faced with unreliable communication and limited battery life (e.g., with aerial rotorcraft). The proposed algorithm utilizes four states: explore, meet, sacrifice, and relay. The explore state uses a frontier-based exploration algorithm, the meet state returns to the last known location of communication to share data, the sacrifice state sends the robot out to explore without consideration of remaining battery, and the relay state lands the robot until a meeting occurs. This approach allows robots to take on the role of a relay to improve communication between team members. In addition, the robots can “sacrifice” themselves by continuing to explore even when they do not have sufficient battery to return to the base station. We compare the performance of the proposed approach to state-of-the-art frontier-based exploration, and results show gains in explored area. The feasibility of components of the proposed approach is also demonstrated on a team of two custom-built quadcopters exploring an office environment.
95 citations
Cites methods from "Signal Strength Coordination for Co..."
...While previous research has focused on exploration algorithms [3], [4] and maintaining mesh networks [5], [6], we focus on coordinating with unreliable communication....
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15 May 2006
TL;DR: An experimental study of strategies for maintaining end-to-end communication links for tasks such as surveillance and search and rescue where team connectivity is essential for providing situational awareness to a base station.
Abstract: Communication is essential for coordination in most cooperative control and sensing paradigms. In this paper, we present an experimental study of strategies for maintaining end-to-end communication links for tasks such as surveillance and search and rescue where team connectivity is essential for providing situational awareness to a base station. We consider the differences between monitoring point-to-point signal strength versus data throughput and present experimental results with our multi-robot testbed in outdoor environments
54 citations
Cites background from "Signal Strength Coordination for Co..."
..., through simulation results, showed in [12] that coordination strategies based on line-of-sight maintenance for cooperative mapping are less efficient than strategies based on inter-agent wireless signal strengths....
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14 Oct 2008
TL;DR: This work presents an integrated system for semi-autonomous cooperative exploration, augmented by an intuitive user interface for efficient human supervision and control, and finds that having a human in the loop improves task performance, especially with larger numbers of robots.
Abstract: Exploration of unknown environments remains one of the fundamental problems of mobile robotics. It is also a prime example for a task that can benefit significantly from multi-robot teams. We present an integrated system for semi-autonomous cooperative exploration, augmented by an intuitive user interface for efficient human supervision and control. In this preliminary study we demonstrate the effectiveness of the system as a whole and the intuitive interface in particular. Congruent with previous findings, results confirm that having a human in the loop improves task performance, especially with larger numbers of robots. Specific to our interface, we find that even untrained operators can efficiently manage a decently sized team of robots.
36 citations
Cites background from "Signal Strength Coordination for Co..."
...Thibodeau et al [15] present a straightforward hierarchical way to organize a group of robots without perfect communication, which we have integrated into our design, extending it to allow for dynamic reallocation of the hierarchy....
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...Thibodeau et al [15] present a straightforward hierarchical way to organize a group of robots without perfect communication, which we have integrated into our design, extending it to...
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References
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Book•
01 Jan 1990TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
Abstract: From the Publisher:
The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures. Like the first edition,this text can also be used for self-study by technical professionals since it discusses engineering issues in algorithm design as well as the mathematical aspects.
In its new edition,Introduction to Algorithms continues to provide a comprehensive introduction to the modern study of algorithms. The revision has been updated to reflect changes in the years since the book's original publication. New chapters on the role of algorithms in computing and on probabilistic analysis and randomized algorithms have been included. Sections throughout the book have been rewritten for increased clarity,and material has been added wherever a fuller explanation has seemed useful or new information warrants expanded coverage.
As in the classic first edition,this new edition of Introduction to Algorithms presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers. Further,the algorithms are presented in pseudocode to make the book easily accessible to students from all programming language backgrounds.
Each chapter presents an algorithm,a design technique,an application area,or a related topic. The chapters are not dependent on one another,so the instructor can organize his or her use of the book in the way that best suits the course's needs. Additionally,the new edition offers a 25% increase over the first edition in the number of problems,giving the book 155 problems and over 900 exercises thatreinforcethe concepts the students are learning.
21,651 citations
Book•
15 Jan 1996
TL;DR: WireWireless Communications: Principles and Practice, Second Edition is the definitive modern text for wireless communications technology and system design as discussed by the authors, which covers the fundamental issues impacting all wireless networks and reviews virtually every important new wireless standard and technological development, offering especially comprehensive coverage of the 3G systems and wireless local area networks (WLANs).
Abstract: From the Publisher:
The indispensable guide to wireless communicationsnow fully revised and updated!
Wireless Communications: Principles and Practice, Second Edition is the definitive modern text for wireless communications technology and system design. Building on his classic first edition, Theodore S. Rappaport covers the fundamental issues impacting all wireless networks and reviews virtually every important new wireless standard and technological development, offering especially comprehensive coverage of the 3G systems and wireless local area networks (WLANs) that will transform communications in the coming years. Rappaport illustrates each key concept with practical examples, thoroughly explained and solved step by step.
Coverage includes:
An overview of key wireless technologies: voice, data, cordless, paging, fixed and mobile broadband wireless systems, and beyond
Wireless system design fundamentals: channel assignment, handoffs, trunking efficiency, interference, frequency reuse, capacity planning, large-scale fading, and more
Path loss, small-scale fading, multipath, reflection, diffraction, scattering, shadowing, spatial-temporal channel modeling, and microcell/indoor propagation
Modulation, equalization, diversity, channel coding, and speech coding
New wireless LAN technologies: IEEE 802.11a/b, HIPERLAN, BRAN, and other alternatives
New 3G air interface standards, including W-CDMA, cdma2000, GPRS, UMTS, and EDGE
Bluetooth wearable computers, fixed wireless and Local Multipoint Distribution Service (LMDS), and other advanced technologies
Updated glossary of abbreviations and acronyms, and a thorolist of references
Dozens of new examples and end-of-chapter problems
Whether you're a communications/network professional, manager, researcher, or student, Wireless Communications: Principles and Practice, Second Edition gives you an in-depth understanding of the state of the art in wireless technologytoday's and tomorrow's.
17,102 citations
"Signal Strength Coordination for Co..." refers background or methods in this paper
...expected from concrete block walls or metal obstacles [19]....
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...To simulate path loss in an environment with obstacles, we use the following model from Rappaport (2001) [19]:...
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...To simulate path loss in an environment with obstacles, we use the following model from Rappaport (2001) [19]: PL(d) = PL(d0) + 20log ( d d0 ) + αd + ∑ i PAFi; (1) where: • d is the distance between the transmitter and the receiver; • PL(d0) is the path loss in dB at a small distanced0 from the…...
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...These behaviors a re due to the effects of multi-path propagation, where multipl e copies of the transmitted signal reach the receiver at sligh tly different times and from different directions [19]....
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Book•
01 Jan 1990
TL;DR: This chapter discusses the configuration space of a Rigid Object, the challenges of dealing with uncertainty, and potential field methods for solving these problems.
Abstract: 1 Introduction and Overview.- 2 Configuration Space of a Rigid Object.- 3 Obstacles in Configuration Space.- 4 Roadmap Methods.- 5 Exact Cell Decomposition.- 6 Approximate Cell Decomposition.- 7 Potential Field Methods.- 8 Multiple Moving Objects.- 9 Kinematic Constraints.- 10 Dealing with Uncertainty.- 11 Movable Objects.- Prospects.- Appendix A Basic Mathematics.- Appendix B Computational Complexity.- Appendix C Graph Searching.- Appendix D Sweep-Line Algorithm.- References.
6,186 citations
"Signal Strength Coordination for Co..." refers background in this paper
...When a robot cannot determine the local gradient of the harmonic function, it re lies on the NF1 navigation function [13] to determine the directi on of motion....
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Book•
01 Feb 1990
TL;DR: Advanced robotics: redundancy and optimization, Advanced robotics: redundancies and optimization , مرکز فناوری اطلاعات و £1,000,000 کسورزی .
Abstract: Advanced robotics: redundancy and optimization , Advanced robotics: redundancy and optimization , مرکز فناوری اطلاعات و اطلاع رسانی کشاورزی
1,137 citations
Additional excerpts
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TL;DR: This paper presents an approach for the coordination of multiple robots, which simultaneously takes into account the cost of reaching a target point and its utility and describes how this algorithm can be extended to situations in which the communication range of the robots is limited.
Abstract: In this paper, we consider the problem of exploring an unknown environment with a team of robots. As in single-robot exploration the goal is to minimize the overall exploration time. The key problem to be solved in the context of multiple robots is to choose appropriate target points for the individual robots so that they simultaneously explore different regions of the environment. We present an approach for the coordination of multiple robots, which simultaneously takes into account the cost of reaching a target point and its utility. Whenever a target point is assigned to a specific robot, the utility of the unexplored area visible from this target position is reduced. In this way, different target locations are assigned to the individual robots. We furthermore describe how our algorithm can be extended to situations in which the communication range of the robots is limited. Our technique has been implemented and tested extensively in real-world experiments and simulation runs. The results demonstrate that our technique effectively distributes the robots over the environment and allows them to quickly accomplish their mission.
1,107 citations
"Signal Strength Coordination for Co..." refers background in this paper
...An example of this is sharing map information so multiple robots do not explore the same area of an environmen t [3, 20, 7]....
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...Exploration tasks can be completed more efficiently when robots share information with each other [3]....
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