Renato Souza de Lira
Papers
1
Total Citations
2
H-Index
1
About
Renato Souza de Lira is a researcher focused on the intersection of robotics and reinforcement learning, with a particular emphasis on autonomous navigation and decision-making systems. His most-cited work, "Robot Training and Navigation through the Deep Q-Learning Algorithm" (2021), demonstrates a practical application of deep reinforcement learning to vehicular robotics. In this study, Lira developed a decision-making framework using the Deep Q-Learning algorithm, enabling a robot to autonomously transport parts through a dynamic environment. This contribution addresses a core challenge in industrial automation: creating adaptive, learning-based navigation systems that can operate without explicit programming. While his citation count (2) reflects a nascent stage in his research trajectory, the work represents a foundational step in integrating advanced AI techniques with real-world robotic tasks. Lira’s research holds promise for advancing autonomous systems in manufacturing and logistics, where efficient, self-learning robots are increasingly critical. His focus on algorithm-driven navigation positions him at the forefront of efforts to make robotics more intelligent and adaptable.
Research Focus
Key Achievements
Top Papers
- 1Robot Training and Navigation through the Deep Q-Learning Algorithm2 citations · 2021