Bio-inspired Patrolling Scheme Design in Wireless and Mobile Sensor and Robot Networks

Zhang, Yanping; Xiao, Yang; Wang, Yun; Mosca, Patrick

doi:10.1007/s11277-016-3607-z

Cited by 5 publications

(4 citation statements)

References 24 publications

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“…Indeed, that grid is extra memory is needed for the IAS-SS strategy, that is, a flag (the cell) for each region in order to indicate the visited areas and the period they are not be monitored. Other approach that uses a grid is the Potential Field Methods (PFM) [39,40]. In this case, the robots are guided to a goal-position and they have a global map.…”

Section: Resultsmentioning

confidence: 99%

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A Multiple Robot Map Building Strategy Using Inverse Ant System-Based Surveillance System

de¹,

Calvo²,

Af³

2018

Int J Robot Eng

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Section: Resultsmentioning

confidence: 99%

“…It was designed to overcome the difficulties of the surveillance task, proofed in [37] to be a NP hard problem. Several approaches present approximate algorithms in known environments and robots' pose [38][39][40]. However, the IAS-SS strategy is independent of environment structure and number of robots.…”

Section: Ias-ssmentioning

confidence: 99%

A Multiple Robot Map Building Strategy Using Inverse Ant System-Based Surveillance System

de¹,

Calvo²,

Af³

2018

Int J Robot Eng

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“…An adaptive ant colony optimization approach for multiple UASs for coordinated trajectory re-planning was proposed by Duan et al [60]. An extension of ACO looks more generically at digital pheromone responses and has been used to improve target search methods [61][62][63]. Shang et al [64] proposed a hybrid algorithm that utilized GA and ACO algorithms for Multi-UAS mission planning which provided performance improvement over the two independent methods.…”

Section: Fixed Targetmentioning

confidence: 99%

Multiple-Scenario Unmanned Aerial System Control: A Systems Engineering Approach and Review of Existing Control Methods

2016

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Abstract:The use of unmanned aerial systems (UASs) in both the public and military environments is predicted to grow significantly. As the demand for UASs grows, the availability of more robust and capable vehicles that can perform multiple mission types will be needed. In the public sector, the demand will grow for UASs to be used for agriculture, forestry, and search and rescue missions. Militaries continue to demand more UAS capabilities for diverse operations around the world. Significant research has been performed and continues to progress in the areas of autonomous UAS control. A majority of the work focuses on subsets of UAS control: path planning, autonomy, small UAS controls, and sensors. Minimal work exists on a system-level problem of multiple-scenario UAS control for integrated systems. This paper provides a high-level modular system architecture definition that is modifiable across platform types and mission requirements. A review of the current research and employment of UAS capabilities is provided to evaluate the state of the capabilities required to enable the proposed architecture.

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“…There has been a significant interest in the mobile robot network composed of mobile robots that cooperate with each other due to its broad range of applications, such as target tracking, 1 advanced manufacturing, 2 disaster rescue, 3 and environment monitoring. 4 And one of the most critical steps about this technology is the simultaneous localization and mapping (SLAM) in an unknown environment. A solution to SLAM problem is beneficial to some special applications where precise environment information is not offered, for example, planetary exploration 5 and aerial vehicles.…”

Section: Introductionmentioning

confidence: 99%

Distributed simultaneous localization and mapping for mobile robot networks via hybrid dynamic belief propagation

Wan

et al. 2017

International Journal of Distributed Sensor Networks

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This article proposes a hybrid dynamic belief propagation for simultaneous localization and mapping in the mobile robot network. The positions of landmarks and the poses of moving robots at each time slot are estimated simultaneously in an online and distributed manner, by fusing the odometry data of each robot and the measurements of robot-robot or robot-landmark relative distance and angle. The joint belief state of all robots and landmarks is encoded by a factor graph and the marginal posterior probability distribution of each variable is inferred by belief propagation. We show how to calculate, broadcast, and update messages between neighboring nodes in the factor graph. Specifically, we combine parametric and nonparametric techniques to tackle the problem arisen from non-Gaussian distributions and nonlinear models. Simulation and experimental results on publicly available dataset show the validity of our algorithm.

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Bio-inspired Patrolling Scheme Design in Wireless and Mobile Sensor and Robot Networks

Cited by 5 publications

References 24 publications

A Multiple Robot Map Building Strategy Using Inverse Ant System-Based Surveillance System

A Multiple Robot Map Building Strategy Using Inverse Ant System-Based Surveillance System

Multiple-Scenario Unmanned Aerial System Control: A Systems Engineering Approach and Review of Existing Control Methods

Distributed simultaneous localization and mapping for mobile robot networks via hybrid dynamic belief propagation

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