Robotics-Based Location Sensing Using Wireless Ethernet

By Andrew M. Ladd, Kostas E. Bekris, Algis Rudys, Lydia E. Kavraki, D. Wallach, Guillaume Marceau. 2002

718 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

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In Computer Networks and Communications

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Citations in the corpus

Method for yielding a database of location fingerprints in WLAN (2005, background): “fingerprint database. Since the variation of the SS measured at each point is large, in order to achieve more accurate results, the probabilistic approach [ 10 , 14] has also been developed.”
The Horus WLAN location determination system (2005, methodology): “Yet, another system, [17], applies the same technique to the robotics domain.”
Accurate GSM Indoor Localization (2005, background): “Most research on indoor localization systems has been based on the use of short-range signals, such as WiFi [3,5,11], Bluetooth [1], ultra sound [15], or infrared [16].”
Kernel-Based Positioning in Wireless Local Area Networks (2007, methodology): “These densities are estimated through either parametric [31] or nonparametric methods [28], [32], [33].”
RSSI-Based Indoor Localization and Tracking Using Sigma-Point Kalman Smoothers (2009, methodology): “These methods estimate probability density for the training RSSI and then compute likelihood/a posteriori estimates during the tracking phase using the observed RSSI and the estimated densities [8], [15], [16].”
Adaptive Temporal Radio Maps for Indoor Location Estimation (2005, methodology): “In the offline phase, aradio mapis built by tabulating the signalstrength values received from the access points at selected locations in the area of interest.”
Detecting 802.11 MAC Layer Spoofing Using Received Signal Strength (2008, background): “report that some RSS distributions are essentially non-Gaussian [11].”
Enhancing Location Privacy in Wireless LAN Through Disposable Interface Identifiers: A Quantitative Analysis (2003, background): “…digital Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for pro.t or commercial advantage and that copies bear this notice and the full citation on the .rst page.”
Power-efficient access-point selection for indoor location estimation (2006, methodology): “Another branch of research is the probabilistic techniques [10], [3], [11], [1], [6] which construct a conditional probability distribution over locations in the environment of interest.”
Modeling of indoor positioning systems based on location fingerprinting (2004, methodology): “This observation of multiple modes has also been made by [13].”
The limits of localization using signal strength: a comparative study (2004, methodology): “Up to this step ABP is very similar to the traditional Bayesian approaches [14], [17], with the exception of the Gaussian and variance assumptions.”
Network-based wireless location: challenges faced in developing techniques for accurate wireless location information (2005, methodology): “But since the IEEE 802.11b and IEEE 802.11g MAC layer software provides the signal strength and the SNR, a software-level location technique could be developed for WLAN networks based on the AmpOA at different access points [58]‐[ 66 ].”
Localization Algorithms and Strategies for Wireless Sensor Networks: Monitoring and Surveillance Techniques for Target Tracking (2009, methodology): “The algorithms selected here span broad techniques that proved practical and useful from surveying the references (Elnahrawy et al., 2004; Bahl et al., 2000; Youssef et al., 2003; Youssef et al., 2004; Battiti et al., 2002; Moore et al., 2004; Fang et al., 2005; Savvides et al., 2001; Lorincz et al.”