Robust method for outdoor localization of a mobile robot using received signal strength in low power wireless networks

Graefenstein, Juergen; Bouzouraa, Mohamed Essayed

doi:10.1109/robot.2008.4543183

Cited by 42 publications

(20 citation statements)

References 10 publications

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“…Therefore, we need to develop an efficient scheme to reduce the redundant forwarding packets. Furthermore, we will conduct real experiments to evaluate the performance of IMAP in the harsh multipath and shadowing environments, the robot will be equipped with an absorbing plate below the antenna to avoid interference with signals reflected by the ground [22]; a more accurate channel propagation model will be considered and studied in this scenario. We will also further evaluate IMAP by comparing the performance of IMAP and other novel location estimation approaches [23], in order to make some improvements.…”

Section: Methodsmentioning

confidence: 99%

Path Planning and Navigation for Mobile Robots in a Hybrid Sensor Network without Prior Location Information

Zhang

et al. 2013

International Journal of Advanced Robotic Systems

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In a hybrid wireless sensor network with mobile and static nodes, which have no prior geographical knowledge, successful navigation for mobile robots is one of the main challenges. In this paper, we propose two novel navigation algorithms for outdoor environments, which permit robots to travel from one static node to another along a planned path in the sensor field, namely the RAC and the IMAP algorithms. Using this, the robot can navigate without the help of a map, GPS or extra sensor modules, only using the received signal strength indication (RSSI) and odometry. Therefore, our algorithms have the advantage of being cost-effective. In addition, a path planning algorithm to schedule mobile robots' travelling paths is presented, which focuses on shorter distances and robust paths for robots by considering the RSSI-Distance characteristics. The simulations and experiments conducted with an autonomous mobile robot show the effectiveness of the proposed algorithms in an outdoor environment.

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Section: Methodsmentioning

confidence: 99%

Path Planning and Navigation for Mobile Robots in a Hybrid Sensor Network without Prior Location Information

Zhang

et al. 2013

International Journal of Advanced Robotic Systems

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“…For a complete discussion on this topic refer to [13,18,19] and references within. In our implementation, z k is populated with the position estimates coming from Min-Max or using Multilateration algorithms, while the velocity algorithm provides speed estimates; x k represents then position and speed estimation according to the physical model described by (4).…”

Section: Velocity-based Trackingmentioning

confidence: 99%

“…The algorithms used to estimate the position from range measurements-such as Min-Max, Multilaterate, Maximum Likelihood, and so forth-are very well known and widely investigated [4]. Unfortunately, many applications are located in indoor scenarios, where the radio channel is mainly unpredictable due to signal's reflections against walls, floors, and ceilings, which cause multipath phenomena [5].…”

Section: Introductionmentioning

confidence: 99%

Low-Complexity Localization and Tracking in Hybrid Wireless Sensor Networks

Kianoush

Goldoni

Savioli

et al. 2012

ISRN Sensor Networks

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Localization in Wireless Sensor Networks (WSNs) is an important research topic: readings come from sensors scattered in the environment, and most of applications assume that the exact position of the sensors is known. Due to power restrictions, WSN nodes are not usually equipped with a global positioning system-hence, many techniques have been developed in order to estimate the position of nodes according to some measurements over the radio channel. In this paper, we propose a new technique to track a moving target by combining distance measurements obtained from both narrowband IEEE 802.15.4 and Ultrawideband (UWB) radios, and then exploiting a novel speed-based algorithm for bounding the error. This process is applied to a real dataset collected during a measurement campaign, and its performance is compared against a Kalman filter. Results show that our algorithm is able to track target path with good accuracy and low computational impact.

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“…In reality, it represents just an approximation procedure which doesn't reflect a real world. Several sensor models have been developed (Tsung-Han, 2008;Awad, 2007;Graefenstein, 2008;Sugano, 2006;Cho, 2007). The most used one can be described by the following equation:…”

Section: Introductionmentioning

confidence: 99%

Position Location Technique in Wireless Sensor Network Using Rapid Prototyping Algorithm

Touati¹,

Aoudia²,

Ali-Chérif³

et al. 2011

Advanced Applications of Rapid Prototyping Technology in Modern Engineering

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Robust method for outdoor localization of a mobile robot using received signal strength in low power wireless networks

Cited by 42 publications

References 10 publications

Path Planning and Navigation for Mobile Robots in a Hybrid Sensor Network without Prior Location Information

Path Planning and Navigation for Mobile Robots in a Hybrid Sensor Network without Prior Location Information

Low-Complexity Localization and Tracking in Hybrid Wireless Sensor Networks

Position Location Technique in Wireless Sensor Network Using Rapid Prototyping Algorithm

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