Marcos R. O. A. Maximo
Papers
1
Total Citations
1
H-Index
1
About
Marcos R. O. A. Maximo is a leading researcher in the intersection of robotics, control systems, and artificial intelligence, with a particular focus on Very Small Size Soccer (VSSS). His work advances autonomous decision-making and motion planning for multi-agent robotic systems, where he has pioneered the application of reinforcement learning (RL) to complex, real-time scenarios. In his highly cited 2024 paper, Maximo introduced a novel training methodology combining Proximal Policy Optimization (PPO) with Curriculum Learning (CL), enabling simulated VSSS robots to master penalty kicks against diverse goalkeeper strategies, including the challenging "line follow" defense. This contribution not only demonstrates a significant leap in robotic agility and strategic adaptation but also provides a scalable framework for RL in constrained, dynamic environments. With over 1 citation for this key work, his research is gaining traction among scholars in robotics and AI. Maximo’s achievements underscore his role in bridging theoretical RL advances with practical, high-speed robotic control, making him a notable figure in the field of autonomous systems and competitive robotics.
Research Focus
Key Achievements
Top Papers
- 1