Generalized geometric triangulation algorithm for mobile robot absolute self-localization

Esteves, João Sena; Carvalho, Adriano; Couto, Carlos

doi:10.1109/isie.2003.1267272

Cited by 56 publications

(50 citation statements)

References 6 publications

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“…When anchor bearings or angular separation between anchors and the mobile node can be obtained, angulation can be used to determine the position of the mobile node [60], [61], [46], [62]. This is pictured in Figure 5b.…”

Section: Localization Phasementioning

confidence: 99%

A Survey on Localization for Mobile Wireless Sensor Networks

Amundson

Koutsoukos

2009

Lecture Notes in Computer Science

255

142

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Abstract. Over the past decade we have witnessed the evolution of wireless sensor networks, with advancements in hardware design, communication protocols, resource efficiency, and other aspects. Recently, there has been much focus on mobile sensor networks, and we have even seen the development of small-profile sensing devices that are able to control their own movement. Although it has been shown that mobility alleviates several issues relating to sensor network coverage and connectivity, many challenges remain. Among these, the need for position estimation is perhaps the most important. Not only is localization required to understand sensor data in a spatial context, but also for navigation, a key feature of mobile sensors. In this paper, we present a survey on localization methods for mobile wireless sensor networks. We provide taxonomies for mobile wireless sensors and localization, including common architectures, measurement techniques, and localization algorithms. We conclude with a description of real-world mobile sensor applications that require position estimation.

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Section: Localization Phasementioning

confidence: 99%

A Survey on Localization for Mobile Wireless Sensor Networks

Amundson

Koutsoukos

2009

Lecture Notes in Computer Science

255

142

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“…Various triangulation algorithms may be found in [1,5,6,7,8,10,11,12,13,14,15,16]. These algorithms can be classified into four groups: (1) Geometric Triangulation, (2) Geometric Circle Intersection, (3) Iterative methods (Iterative Search, Newton-Raphson, etc), and (4) Multiple Beacons Triangulation.…”

Section: Related Workmentioning

confidence: 99%

“…Triangulation is the process of determining the location of a point by measuring angles to it from known points, while trilateration methods involve the determination of absolute or relative locations of points by measurement of distances. Because of the large variety of angle measurement systems, triangulation has emerged as a widely used, robust, accurate, and flexible technique [10]. Another advantage of triangulation versus trilateration is that the robot can compute its orientation (or heading) in addition to its position, so that the complete pose of the robot can be found.…”

Section: Introductionmentioning

confidence: 99%

A New Three Object Triangulation Algorithm Based on the Power Center of Three Circles

Pierlot

Urbin-Choffray

Droogenbroeck

2011

Communications in Computer and Information Science

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V. PIERLOT, M. VAN DROOGENBROECK, and M. Urbin-Choffray. A new three object triangulation algorithm based on the power center of three circles. Abstract Positioning is a fundamental issue in mobile robot applications that can be achieved in multiple ways. Among these methods, triangulation is a proven technique. As it exists for a long time, many variants of triangulation have been proposed. Which variant is most appropriate depends on the application because some methods ignore the beacon ordering while other have blind spots. Some methods are reliable but at a price of increasing complexity or special cases study. In this paper, we present a simple and new three object triangulation algorithm. Our algorithm works in the whole plane (except when the beacons and the robot are concyclic or colinear), and for any beacon ordering. Moreover, it does not need special cases study and has a strong geometrical meaning. Benchmarks show that our algorithm is faster than existing and comparable algorithms. Finally, a quality measure is intrinsically derived for the triangulation result in the whole plane, which can be used to identify the pathological cases, or as a validation gate in Kalman filters.

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“…Two such reference positions (or three non-collinear ones in degenerate cases) are enough to localize any number of nodes within range. In [2], a method is given to determine position based on the angular separation (the difference in bearings) between beacons. Other angle of arrival positioning approaches have been developed, including multiangulation using subspace methods [4], anchor bearing propagation [1], and semidefinite programming [3].…”

Section: Related Workmentioning

confidence: 99%

“…Although several techniques exist for determining node position based on bearing information [1], [2], [3], [4], [5], there are few options for actually measuring signal AOA in WSNs. Currently available methods for bearing estimation require a heavy-weight infrastructure [6], rotating hardware [7], [8], directional antennas [9], and/or expensive and sophisticated sensors [10].…”

Section: Introductionmentioning

confidence: 99%

Radio Interferometric Angle of Arrival Estimation

Amundson

Sallai

Koutsoukos

et al. 2010

Lecture Notes in Computer Science

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Abstract. Several localization algorithms exist for wireless sensor networks that use angle of arrival measurements to estimate node position. However, there are limited options for actually obtaining the angle of arrival using resource-constrained devices. In this paper, we describe a radio interferometric technique for determining bearings from an anchor node to any number of target nodes at unknown positions. The underlying idea is to group three of the four nodes that participate in a typical radio interferometric measurement together to form an antenna array. Two of the nodes transmit pure sinusoids at close frequencies that interfere to generate a low-frequency beat signal. The phase difference of the measured signal between the third array node and the target node constrains the position of the latter to a hyperbola. The bearing of the node can be estimated by the asymptote of the hyperbola. The bearing estimation is carried out by the node itself, hence the method is distributed, scalable and fast. Furthermore, this technique does not require modification of the mote hardware because it relies only on the radio. Experimental results demonstrate that our approach can estimate node bearings with an accuracy of approximately 3 • in 0.5 sec.

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Generalized geometric triangulation algorithm for mobile robot absolute self-localization

Cited by 56 publications

References 6 publications

A Survey on Localization for Mobile Wireless Sensor Networks

A Survey on Localization for Mobile Wireless Sensor Networks

A New Three Object Triangulation Algorithm Based on the Power Center of Three Circles

Radio Interferometric Angle of Arrival Estimation

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