Fausto Guzzo da Costa
Papers
2
Total Citations
18
H-Index
2
About
Fausto Guzzo da Costa’s research lies at the intersection of robotics, artificial intelligence, and wireless communications, with a primary focus on indoor robotic localization. His work addresses the critical challenge of enabling autonomous robots to navigate indoor environments without relying on GPS, which is often unavailable or unreliable in such settings. Guzzo da Costa’s major contribution is the development of an autonomous localization system that leverages artificial neural networks (ANNs) evolved using information from wireless networks (WN). By designing and building a system that processes signal strength data from Wi-Fi or similar networks, he demonstrated how ANNs can be trained to estimate a robot’s position with increasing accuracy over time. His two most-cited papers, “INVESTIGATION ON THE EVOLUTION OF AN INDOOR ROBOTIC LOCALIZATION SYSTEM BASED ON WIRELESS NETWORKS” (2013) and “Evolving an Indoor Robotic Localization System Based on Wireless Networks” (2012), each with 9 citations, form the backbone of this work. Though modest in citation count, these studies represent foundational steps in a niche area, offering a cost-effective, scalable alternative to traditional sensor-based localization. Guzzo da Costa’s research is particularly notable for its practical approach, bridging machine learning and embedded systems to solve real-world navigation problems.
Research Focus
Key Achievements
Top Papers
- 1
- 2