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In this paper we combine the Iterative Closest Point (’ICP’) and ‘point-to-plane ICP‘ algorithms into a single probabilistic framework. We then use this framework to model locally planar surfaceExpand
Gaussian Processes for Signal Strength-Based Location Estimation
Gaussian processes can be used to generate a likelihood model for signal strength measurements and parameters of the model, such as signal noise and spatial correlation between measurements, can be learned from data via hyperparameter estimation. Expand
Mapping and localization with RFID technology
A probabilistic measurement model for RFID readers that allow us to accurately localize RFID tags in the environment and demonstrates how such maps can be used to localize a robot and persons in their environment. Expand
Junior: The Stanford Entry in the Urban Challenge
The architecture of Junior, a robotic vehicle capable of navigating urban environments autonomously, successfully finished and won second place in the DARPA Urban Challenge, a robot competition organized by the U.S. Government. Expand
An efficient fastSLAM algorithm for generating maps of large-scale cyclic environments from raw laser range measurements
In this paper a novel algorithm that combines Rao-Blackwellized particle filtering and scan matching is presented, which reduces the particle depletion problem that typically prevents the robot from closing large loops. Expand
Practical Metropolitan-Scale Positioning for GSM Phones
This paper examines the positioning accuracy of a GSM beacon-based location system in a metropolitan environment and shows that a small 60-hour calibration drive is sufficient for enabling a metropolitan area similar to Seattle. Expand
Experiences with an Interactive Museum Tour-Guide Robot
The software architecture of an autonomous, interactive tour-guide robot is presented, which integrates localization, mapping, collision avoidance, planning, and various modules concerned with user interaction and Web-based telepresence and enables robots to operate safely, reliably, and at high speeds in highly dynamic environments. Expand
MINERVA: a second-generation museum tour-guide robot
An interactive tour-guide robot is described, which was successfully exhibited in a Smithsonian museum, and uses learning pervasively at all levels of the software architecture to address issues such as safe navigation in unmodified and dynamic environments, and short-term human-robot interaction. Expand
The Interactive Museum Tour-Guide Robot
It is argued that time is ripe for the development of AI-based commercial service robots that assist people in everyday life. Expand
Inferring activities from interactions with objects
The key observation is that the sequence of objects a person uses while performing an ADL robustly characterizes both the ADL's identity and the quality of its execution. Expand