Renie A. Delgado
Papers
1
Total Citations
7
H-Index
1
About
Renie A. Delgado is a researcher working at the intersection of robotics, reinforcement learning, and autonomous systems, with a particular focus on sim-to-real transfer in competitive robotic environments. Their most notable contribution is the development of VSSS-RL, an open framework designed to advance the study of reinforcement learning within the context of the IEEE Very Small Size Soccer (VSSS) league. This work addresses one of the most pressing challenges in modern robotics: bridging the gap between simulated training environments and real-world deployment. By providing a structured platform supporting both continuous and discrete control policy training, Delgado's framework empowers researchers and students to experiment with RL techniques in a standardized, accessible setting. Published in 2020, this foundational work has accumulated 7 citations, reflecting growing interest from the robotics and machine learning communities. Delgado's research is particularly valuable for those exploring multi-agent coordination, autonomous decision-making, and the practical limitations of simulation-based training. Their contributions offer an important stepping stone for the broader robotics community seeking reproducible, open-source methodologies for advancing intelligent autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1