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— Estimating the location of a mobile device or a robot from wireless signal strength has become an area of highly active research. The key problem in this context stems from the complexity of how signals propagate through space, especially in the presence of obstacles such as buildings, walls or people. In this paper we show how Gaussian processes can be(More)
WiFi localization, the task of determining the physical location of a mobile device from wireless signal strengths, has been shown to be an accurate method of indoor and outdoor localization and a powerful building block for location-aware applications. However, most localization techniques require a training set of signal strength readings labeled against(More)
The goal of this research is to enable mobile robots to navigate through crowded environments such as indoor shopping malls, airports, or downtown side walks. The key research question addressed in this paper is how to learn planners that generate human-like motion behavior. Our approach uses inverse reinforcement learning (IRL) to learn human-like(More)
Public transit systems play an important role in combating traffic congestion, reducing carbon emissions, and promoting compact, sustainable urban communities. The usability of public transit can be significantly enhanced by providing good traveler information systems. We describe OneBusAway, a set of transit tools focused on providing real-time arrival(More)
— We studied an indoor wayfinding application for individuals with cognitive impairments using Wizard-of-Oz techniques. This gave us insights into the technological considerations for the location system underlying such an application. We have abstracted these into generally desirable properties for location-aware systems for wayfinding. In addition to(More)