Vinu Maddumage
Papers
1
Total Citations
1
H-Index
1
About
Vinu Maddumage is a researcher advancing the field of socially-aware mobile robotics, with a focus on enabling autonomous systems to navigate safely and intuitively in human-shared environments. His key research areas include deep reinforcement learning (DRL), human-robot interaction, and reward model design for crowd navigation. Maddumage’s major contribution is the development of a **Relative Velocity-Based Reward Model**, a novel framework that integrates human motion dynamics into DRL training to produce more natural, collision-free navigation policies. This work directly addresses the challenge of robots moving among pedestrians without causing discomfort or disruption. While his most-cited paper, published in 2025, has already garnered early attention with 1 citation, its conceptual foundation holds strong potential for influencing future socially-aware systems. Maddumage’s research stands out for its practical emphasis on real-world deployment, bridging the gap between simulation-based learning and actual human-robot interaction. His work is particularly relevant for students and engineers interested in the intersection of reinforcement learning, robotics, and human-centered design, offering a clear pathway toward more cooperative and context-aware autonomous agents.
Research Focus
Key Achievements
Top Papers
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