Abstract | ||
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This paper investigates two new groups of trajectory optimization problems which stem from networked multi-robotic systems. In particular, we study how to efficiently collect data from stationary sensor nodes using multiple robotic vehicles such as data ferries under different circumstance. The first group includes two new problems which aim to find the tours and the paths, respectively, of k robot vehicles with different mobilization conditions to collect data from ground sensor nodes with minimum latency. The second group consists of one new problem whose goal is to determine the quality tours of k robot vehicles with different speeds, where each of which follows its corresponding tour to repeatedly collect data from stationary sensors. We prove the three problems are NP-hard and propose constant factor approximation strategies for them. Through a simulation, an analytical study is conducted to evaluate the average performance of our core contribution. |
Year | DOI | Venue |
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2014 | 10.1109/INFOCOM.2014.6848171 | INFOCOM |
Keywords | Field | DocType |
approximation algorithm,mobile elements,constant factor approximation strategies,multiple robotic vehicles,approximation theory,travelling salesman problems,trajectory optimization problems,np-hard problem,stationary sensor nodes,wireless sensor network,mobilization conditions,mobile robots,multi-robot systems,unmanned aerial vehicles,computational complexity,path planning,trajectory control,multiple heterogeneous data ferry trajectory planning,minimum latency,traveling salesperson problem,quality tours,graph theory,wireless sensor networks,networked multirobotic systems,data collection | Key distribution in wireless sensor networks,Trajectory optimization,Latency (engineering),Computer science,Mobile wireless sensor network,Robot,Wireless sensor network,Distributed computing,Trajectory planning | Conference |
ISSN | Citations | PageRank |
0743-166X | 11 | 0.61 |
References | Authors | |
22 | 6 |
Name | Order | Citations | PageRank |
---|---|---|---|
Lirong Xue | 1 | 12 | 0.96 |
Kim Donghyun | 2 | 458 | 41.00 |
Zhu Yuqing | 3 | 467 | 37.26 |
Deying Li | 4 | 1216 | 101.10 |
Wei Wang 0032 | 5 | 13 | 0.97 |
Alade O. Tokuta | 6 | 159 | 13.96 |