Papers
11
Total Citations
170
H-Index
8
About
R. Flores is a pioneering researcher in indoor robotics navigation, whose work fundamentally advanced the use of WiFi signal measurements for autonomous robot localization and control. His key research areas include probabilistic robotics, sensor fusion, and intelligent diagnostic systems for autonomous vehicles. Flores made his most significant contribution by being the first to integrate WiFi signal strength as an observation within a Partially Observable Markov Decision Process (POMDP) framework, a breakthrough that enabled robots to navigate indoor environments without expensive infrastructure. His seminal 2005 paper on this approach has garnered 62 citations, establishing a foundation for cost-effective indoor localization. Flores further refined this work by combining WiFi with ultrasound observations and developing automatic training methods using the Baum-Welch algorithm, achieving robust navigation in complex corridor environments. Beyond navigation, he contributed to knowledge-based collision diagnosis for ground robots and people location systems using WiFi signals. His research, spanning from 2003 to 2009, produced over 150 citations across ten publications, demonstrating lasting impact on the fields of mobile robotics and wireless sensor-based localization.
Research Focus
Key Achievements
Top Papers
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- 5Low level controller for a POMDP based on WiFi observations11 citations · 2006
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- 7Training Method Improvements of a WiFi Navigation System Based on POMDP10 citations · 2006
- 8People Location System based on WiFi Signal Measure9 citations · 2007
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