A probabilistic model of integration
Decision Support Systems
Data gathering tours for mobile robots
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Using mobile robots to harvest data from sensor fields
IEEE Wireless Communications
Racetrack: an approximation algorithm for the mobile sink routing problem
ADHOC-NOW'10 Proceedings of the 9th international conference on Ad-hoc, mobile and wireless networks
Fast track article: Designing hierarchical sensor networks with mobile data collectors
Pervasive and Mobile Computing
Path Planning of Data Mules in Sensor Networks
ACM Transactions on Sensor Networks (TOSN)
Robot routing in sparse wireless sensor networks with continuous ant colony optimization
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Review: From wireless sensor networks towards cyber physical systems
Pervasive and Mobile Computing
Staying-alive path planning with energy optimization for mobile robots
Expert Systems with Applications: An International Journal
Efficient data collection from wireless nodes under the two-ring communication model
International Journal of Robotics Research
An evolutionary approach for the dubins' traveling salesman problem with neighborhoods
Proceedings of the 14th annual conference on Genetic and evolutionary computation
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Given a set of sparsely distributed sensors in the Euclidean plane, a mobile robot is required to visit all sensors to download the data and finally return to its base. The effective range of each sensor is specified by a disk and the robot must at least reach the boundary to start communication. The primary goal of optimization in this scenario is to minimize the traveling distance by the robot. This problem can be regarded as a special case of the Traveling Salesman Problem with Neighborhoods (TSPN), which is known to be NP-hard. In this paper, we present a novel TSPN algorithm for this class of TSPN, which can yield significantly improved results compared to the latest approximation algorithm.