F. Javier Toledo
Papers
1
Total Citations
17
H-Index
1
About
F. Javier Toledo is a researcher in mobile robotics, whose work focuses on sensor-based navigation and environmental perception for autonomous systems. His most-cited paper, "Map building with ultrasonic sensors of indoor environments using neural networks" (2002, 17 citations), addresses fundamental challenges in mobile robot navigation by developing a method to construct global maps of indoor spaces using ultrasonic sensors. This work contributes to key tasks such as position estimation and path planning, leveraging neural networks to interpret sensor data and generate reliable representations of the robot’s surroundings. Toledo’s research is notable for its practical approach to low-cost sensing, enabling robots to operate effectively in real-world environments without relying on expensive equipment. While his citation count reflects a focused and specialized impact, his contributions are valuable for researchers working on autonomous navigation, sensor fusion, and neural network applications in robotics. His work remains relevant for students and engineers seeking to understand how simple sensors can be harnessed for complex mapping tasks, bridging the gap between theoretical algorithms and practical robotic systems.
Research Focus
Key Achievements
Top Papers
- 1