Tommaso Van Der Meer
Papers
1
Total Citations
2
H-Index
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About
Tommaso Van Der Meer is a rising researcher at the forefront of social robotics and human-robot interaction, with a specialized focus on developing safe, efficient navigation strategies for robots operating in human-populated environments. His work centers on the critical challenge of human motion modeling within reinforcement learning frameworks, addressing a fundamental bottleneck in social robot navigation: how robots can accurately predict and adapt to the unpredictable movements of people in real-time. Van Der Meer’s most cited paper, "A Comparative Study of Human Motion Models in Reinforcement Learning Algorithms for Social Robot Navigation" (2025), systematically evaluates how different human motion representations impact the performance of navigation algorithms, providing a foundational benchmark for the field. Though early in his career, his contributions are already shaping the design of more socially-aware autonomous systems. By bridging the gap between theoretical motion models and practical reinforcement learning applications, Van Der Meer is helping to lay the groundwork for robots that can navigate crowded spaces—from hospital corridors to public squares—with the grace and safety that human-robot coexistence demands.
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Top Papers
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