Maxwell Svetlik
Papers
6
Total Citations
330
H-Index
5
About
Maxwell Svetlik is a robotics and artificial intelligence researcher whose work spans human-robot interaction, grounded language learning, and robotic manipulation. His research is distinguished by a commitment to building practical, deployable systems that bridge theoretical AI advances with real-world robot performance. Svetlik's most recognized contribution is the BWIBots platform (2017, 115 citations), a custom multi-robot system designed to close the gap between AI research and human-robot interaction, enabling robots to execute complex, long-horizon service tasks in open environments. Complementing this systems-level work, his research on 6-DoF grasp detection via implicit representations (2021, 114 citations) demonstrates sophisticated reasoning about 3D scene geometry under noisy, incomplete perception — a critical challenge in robotic manipulation within cluttered environments. His earlier work on multi-modal grounded language learning (2016, 70 citations) pushed beyond vision-only approaches by incorporating haptic, auditory, and proprioceptive signals, allowing robots to understand language through richer sensory experience. Related research on ordinal object relations through exploratory behavior further reflects his interest in how robots learn nuanced, context-dependent properties of the physical world. More recently, Svetlik has contributed to open-source frameworks for last-mile delivery with heterogeneous robot teams, underscoring a broader commitment to accessible, real-world robotic solutions.
Research Focus
Key Achievements
Top Papers
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- 3Learning multi-modal grounded linguistic semantics by playing I Spy70 citations · 2016
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