Reliable location sensing through multi-sensor fusion, dynamic weighting, and confidence mapping

Ubiquitous computing environments provide multitudes of technologies seamlessly augmented with physical systems to aid users in everyday tasks. In order for these systems to be pervasive and yet imperceptible to the user, they must maintain the location of users, devices, and resources within the room. Real-world systems are dynamic and constantly changing, with mobile people and devices. Current location sensing trends within pervasive systems focus on heterogeneous and hybrid systems that consist of multiple location sensing technologies. Fusing the information from these technologies continues to be a focus of current research. Several problems arise from current approaches to this problem. First, current approaches rely on statically assigned confidences to sensor systems. Obtaining confidence information about sensor technologies in realistic environments remains a difficult challenge. Currently, the analysis of location-sensing technologies occurs under idealized and hypothetical environments, largely ignoring dynamic, environment-specific problems. Current probabilistic approaches improve overall results, but they still lack robustness to the weaknesses inherent in the technologies. Each location sensing system fails to provide reliably accurate results under certain system and environment specific circumstances and scenarios. Due to this, reliable location-awareness requires the fusion of heterogeneous location-sensing systems. We provide a method for dynamically evaluating systems in realistic environments, making it possible to optimize the setup of sensor systems (such as camera placement for vision tracking). Integrating internal sensor error information with multiple location sensor technologies, we provide a system for obtaining reliably accurate location information.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2010

Author dc:creator

• Naisbitt, Jeffrey D.

Contributors dc:contributor

• Campbell, Roy H.

• location-sensing
• tracking
• sensor fusion

Statement dc:rights

• Copyright Jeffrey D. Naisbitt

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/14686

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/14686