scholarly journals Indoor Surveillance Application using Wireless Robots and Sensor Networks

Robotics ◽  
2013 ◽  
pp. 838-875
Author(s):  
Anis Koubaa ◽  
Sahar Trigui ◽  
Imen Chaari
Keyword(s):  
Sensor Networks ◽  
Path Planning ◽  
Mobile Robots ◽  
Task Allocation ◽  
Wireless Sensor ◽  
Robot Path Planning ◽  
Research Fields ◽  
Robot Task ◽  
Pervasive Applications ◽  
Surveillance Application

Mobile robots and Wireless Sensor Networks (WSNs) are enabling technologies of ubiquitous and pervasive applications. Surveillance is one typical example of such applications for which the literature proposes several solutions using mobile robots and/or WSNs. However, robotics and WSNs have mostly been considered as separate research fields, and little work has investigated the marriage of these two technologies. In this chapter, the authors propose an indoor surveillance application, SURV-TRACK, which controls a team of multiple cooperative robots supported by a WSN infrastructure. They propose a system model for SURV-TRACK to demonstrate how robots and WSNs can complement each other to efficiently accomplish the surveillance task in a distributed manner. Furthermore, the authors investigate two typical underlying problems: (1) Multi-Robot Task Allocation (MRTA) for target tracking and capturing and (2) robot path planning. The novelty of the solutions lies in incorporating a WSN in the problems’ models. The authors believe that this work advances the literature by demonstrating a concrete ubiquitous application that couples robotic and WSNs and proposes new solutions for path planning and MRTA problems.

Indoor Surveillance Application using Wireless Robots and Sensor Networks

2013 ◽  
pp. 19-57
Author(s):  
Anis Koubaa ◽  
Sahar Trigui ◽  
Imen Chaari
Keyword(s):  
Sensor Networks ◽  
Path Planning ◽  
Mobile Robots ◽  
Task Allocation ◽  
Wireless Sensor ◽  
Robot Path Planning ◽  
Research Fields ◽  
Robot Task ◽  
Pervasive Applications ◽  
Surveillance Application

Mobile robots and Wireless Sensor Networks (WSNs) are enabling technologies of ubiquitous and pervasive applications. Surveillance is one typical example of such applications for which the literature proposes several solutions using mobile robots and/or WSNs. However, robotics and WSNs have mostly been considered as separate research fields, and little work has investigated the marriage of these two technologies. In this chapter, the authors propose an indoor surveillance application, SURV-TRACK, which controls a team of multiple cooperative robots supported by a WSN infrastructure. They propose a system model for SURV-TRACK to demonstrate how robots and WSNs can complement each other to efficiently accomplish the surveillance task in a distributed manner. Furthermore, the authors investigate two typical underlying problems: (1) Multi-Robot Task Allocation (MRTA) for target tracking and capturing and (2) robot path planning. The novelty of the solutions lies in incorporating a WSN in the problems’ models. The authors believe that this work advances the literature by demonstrating a concrete ubiquitous application that couples robotic and WSNs and proposes new solutions for path planning and MRTA problems.

A Bending Beam-Based Path Planning Method Suitable for Mobile Robots in Sensor Network Environments

2007 ◽  
Author(s):  
Yu Zhou
Keyword(s):  
Sensor Networks ◽  
Path Planning ◽  
Mobile Robots ◽  
Sensor Network ◽  
Sensor Node ◽  
Planning Method ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Beam Deflection ◽  
Robot Path

This paper introduces a novel distributive path planning method, the bending beam method, for mobile robots moving in environments monitored by wireless sensor networks. The proposed method is inspired by the deflection analysis of bending beams. The initial and goal positions of a mobile robot are connected by a virtual beam. The in-between obstacles are replaced with the effective loads acting on the beam. The resulting robot path is represented by the deflection curve of the beam under those loads. Following the principle of superposition, the beam deflection under all the loads is equal to the sum of the deflections caused by the individual loads acting on the beam separately. In an environment covered by a wireless sensor network, each sensor node monitors the obstacles (stationary and moving) in its neighborhood. By letting each sensor node compute the deflections of the virtual beam caused by only those neighboring obstacles, the computation load for the global robot path planning can be distributed among the sensor nodes. Thus, the path planning becomes a highly parallel computation procedure. The robot only needs to collect the results from the sensor nodes and sum them up to generate its path. Moreover, the robot path can be dynamically modified by the sensor nodes in the case of moving obstacles. As a result, the proposed method may substantially reduce the time complexity of the sensor-based motion planning for mobile robots in dynamic environments, with the assistance from sensor networks.

An Obstacle-resistant Relay Node Placement in Constrained Environment

2019 ◽  
Author(s):  
Abhishek Verma ◽  
Virender Ranga
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Mobile Robots ◽  
Relay Node ◽  
Wireless Sensor ◽  
Relay Node Placement ◽  
Node Placement ◽  
Simulation Results ◽  
Additional Hardware ◽  
Shape And Size

Relay node placement in wireless sensor networks for constrained environment is a critical task due to various unavoidable constraints. One of the most important constraints is unpredictable obstacles. Handling obstacles during relay node placement is complicated because of complexity involved to estimate the shape and size of obstacles. This paper presents an Obstacle-resistant relay node placement strategy (ORRNP). The proposed solution not only handles the obstacles but also estimates best locations for relay node placement in the network. It also does not involve any additional hardware (mobile robots) to estimate node locations thus can significantly reduce the deployment costs. Simulation results show the effectiveness of our proposed approach.

A Novel Static Path Planning Method for Mobile Anchor-Assisted Localization in Wireless Sensor Networks

2020 ◽  
Vol 10 ◽  
Author(s):  
Abdelhady M. Naguib ◽  
Shahzad Ali
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Path Planning ◽  
Sensor Node ◽  
Large Scale ◽  
Performance Metrics ◽  
Wireless Sensor ◽  
Anchor Node ◽  
Mobile Anchor ◽  
Planning Methods

Background: Many applications of Wireless Sensor Networks (WSNs) require awareness of sensor node’s location but not every sensor node can be equipped with a GPS receiver for localization, due to cost and energy constraints especially for large-scale networks. For localization, many algorithms have been proposed to enable a sensor node to be able to determine its location by utilizing a small number of special nodes called anchors that are equipped with GPS receivers. In recent years a promising method that significantly reduces the cost is to replace the set of statically deployed GPS anchors with one mobile anchor node equipped with a GPS unit that moves to cover the entire network. Objectives: This paper proposes a novel static path planning mechanism that enables a single anchor node to follow a predefined static path while periodically broadcasting its current location coordinates to the nearby sensors. This new path type is called SQUARE_SPIRAL and it is specifically designed to reduce the collinearity during localization. Results: Simulation results show that the performance of SQUARE_SPIRAL mechanism is better than other static path planning methods with respect to multiple performance metrics. Conclusion: This work includes an extensive comparative study of the existing static path planning methods then presents a comparison of the proposed mechanism with existing solutions by doing extensive simulations in NS-2.

scholarly journals A Survey of Task Allocation: Contrastive Perspectives From Wireless Sensor Networks and Mobile Crowdsensing

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 78406-78420 ◽  
Author(s):  
Wenzhong Guo ◽  
Weiping Zhu ◽  
Zhiyong Yu ◽  
Jiangtao Wang ◽  
Bin Guo
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Task Allocation ◽  
Wireless Sensor ◽  
Mobile Crowdsensing
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