Guilherme Pauli
Papers
2
Total Citations
4
H-Index
1
About
Guilherme Pauli is a researcher at the forefront of intelligent robotics, with a specialized focus on the high-speed, multi-agent domain of robot soccer. His work is centered on solving critical challenges in the Small Size League (SSL), a category defined by its dynamic, real-time decision-making demands. Pauli’s major contributions lie in enhancing robotic perception and strategic anticipation. In his foundational work, "Solving the Time Lapse from Vision System in a Robot Soccer Game Using Kalman Filter" (2019, 3 citations), he addressed a core latency problem, developing robust state estimation to bridge the gap between visual updates and the rapid pace of gameplay. Building on this, his more recent and notable paper, "Learning Long-Term Dependencies to Predict an Opponent’s Behavior in Robot Soccer" (2025, 1 citation), introduces a novel deep learning approach. This work marks a significant leap forward, enabling robots to not just react, but to proactively anticipate and counter opponent strategies by learning complex, long-term behavioral patterns. Through this blend of filtering and predictive AI, Pauli is pushing the boundaries of autonomous, collaborative decision-making in one of robotics’ most challenging testbeds.
Research Focus
Key Achievements
Top Papers
- 1
- 2