Study on cooperative positioning system: optimum moving strategies for CPS-III

Kurazume, Ryo; Hirose, Shigeo

doi:10.1109/robot.1998.680642

Cited by 67 publications

(42 citation statements)

References 7 publications

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“…The teams then exchange roles and the process continues until both teams have reached their target. Improvements over this system and optimum motion strategies are discussed in [17,15,16]. Similarly, in [11], only one robot moves, while the rest of the team of small-sized robots forms an equilateral triangle of localization beacons in order to update their pose estimates.…”

Section: Related Workmentioning

confidence: 99%

Propagation of Uncertainty in Cooperative Multirobot Localization: Analysis and Experimental Results

Roumeliotis¹,

Rekleitis²

2004

Autonomous Robots

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Abstract. This paper examines the problem of cooperative localization for the case of large groups of mobile robots. A Kalman filter estimator is implemented and tested for this purpose. The focus of this paper is to examine the effect on localization accuracy of the number N of participating robots and the accuracy of the sensors employed. More specifically, we investigate the improvement in localization accuracy per additional robot as the size of the team increases. Furthermore, we provide an analytical expression for the upper bound on the positioning uncertainty increase rate for a team of N robots as a function of N , the odometric and orientation uncertainty for the robots, and the accuracy of a robot tracker measuring relative positions between pairs of robots. The analytical results derived in this paper are validated both in simulation and experimentally for different test cases.

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Section: Related Workmentioning

confidence: 99%

Propagation of Uncertainty in Cooperative Multirobot Localization: Analysis and Experimental Results

Roumeliotis¹,

Rekleitis²

2004

Autonomous Robots

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“…Kurazume and Hirose [12] propose a leapfrogging strategy for a team of robots comprised with one master and two slave robots. The master and slave robots alternate in moving forward on straight paths toward a destination, while the slave robots act as portable landmarks for localizing the master robot.…”

Section: Related Workmentioning

confidence: 99%

“…where the weighting matrix (11)] is a function of the control input v F mk , the prior covariance P k+1|k [see (12)] is also a function of the optimization variablep k+1|k , which makes solving the optimization problem very challenging. However, since the robots are required to move in formation, the follower can only deviate from the nominal position p o by a small distance r. So we approximate the prior covariance by a constant matrix P which is chosen to be the prior covariance when the follower moves to the desired position p o .…”

Section: Optimization Problem Formulationmentioning

confidence: 99%

Optimized motion strategies for localization in leader-follower formations

Zhou¹,

Roumeliotis²

2011

2011 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-This paper addresses the problem of determining the optimal robot trajectory for localizing a robot follower in a leader-follower formation using robot-to-robot distance or bearing measurements. In particular, maintaining a perfect formation has been shown to reduce the localization accuracy (as compared to moving randomly), or even leads to loss of observability when only distance or bearing measurements are available and the robots move on parallel straight lines. To address this limitation, we allow the follower to slightly deviate from its desired formation-imposed position and seek to find the next best location where it should move to in order to minimize the uncertainty about its relative, with respect to the leader, position and orientation estimates. We formulate and solve this non-convex optimization problem analytically and show, through extensive simulations, that the proposed optimized motion strategy leads to significant localization accuracy improvement as compared to competing approaches.

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“…for localization was proposed by Kurazume et al as a more Finally, one of the most intriguing aspects of modular robots accurate and robust alternative to robot positioning via dead is the notion that the constituent modules of a robot could be reckoning [2,3,4]. The procedure was termed Cooperative reorganized or reconfigured depending on the dictates of the Positioning (CP).…”

Section: Robots Self Assemblymentioning

confidence: 99%

“…They showed far superior positioning results to those obtained from dead reckoning [3,4]. Grabowski et al [6] also implemented a planar version Fig 1. Each cluster in the modular robot is composed of four of a comparable scheme using the "Millibots" platforms.…”

Section: Robots Self Assemblymentioning

confidence: 99%

Using Smart Cameras to Localize Self-Assembling Modular Robots

Shirmohammadi

Yim

Sastra

et al. 2007

2007 First ACM/IEEE International Conference on Distributed Smart Cameras

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In order to realize the goal of self assembling or self reconfiguring modular robots the constituent modules in the system need to be able to gauge their position and orientation with respect to each other. This paper describes an approach to solving this localization problem by equipping each of the modules in the ensemble with a smart camera system. The paper describes one implementation of this scheme on a modular robotic system and discusses the results of a self assembly experiment. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Pennsylvania's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. ABSTRACT to using self localizing smart camera systems to provide this In order to realize the goal of self assembling or self reconpositioning information. figuring modular robots the constituent modules in the sysIn this paper we describe how self localization techniques tem need to be able to gauge their position and orientation originally developed for automatically localizing collections with respect to each other. This paper describes an approach of distributed smart cameras [1] can be adapted to localize to solving this localization problem by equipping each of the modular robotic components and, hence, to facilitate these modules in the ensemble with a smart camera system. The patypes of self assembly operations. In the proposed scheme, per describes one implementation of this scheme on a modueach of the modular components is equipped with a smart lar robotic system and discusses the results of a self assembly camera system and a controllable light source. The modules experiment.use the lights to signal to each other and they determine their Index Terms-Smart Cameras, Localization, Modular relative pose from the available image measurements.

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Study on cooperative positioning system: optimum moving strategies for CPS-III

Cited by 67 publications

References 7 publications

Propagation of Uncertainty in Cooperative Multirobot Localization: Analysis and Experimental Results

Propagation of Uncertainty in Cooperative Multirobot Localization: Analysis and Experimental Results

Optimized motion strategies for localization in leader-follower formations

Using Smart Cameras to Localize Self-Assembling Modular Robots

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