Arjun Gupta

Papers

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About

Arjun Gupta is a leading researcher in robotics and spatial perception, with a focus on creating intelligent systems that understand and navigate complex, dynamic environments. His work centers on simultaneous localization and mapping (SLAM), 3D scene understanding, and the development of hierarchical representations for autonomous agents. Gupta’s most notable contribution is the Kimera framework, introduced in his highly cited 2021 paper, which integrates SLAM with spatial perception to build 3D dynamic scene graphs. This groundbreaking system allows robots to construct rich, multi-layered mental models of their surroundings—capturing not just geometry but also semantic information like objects, rooms, and buildings, while tracking static and dynamic entities and their relationships. With over 12 citations, this work has become a foundational reference for researchers aiming to bridge low-level sensing and high-level reasoning in robotics. Gupta’s achievements highlight his impact on advancing autonomous navigation and human-robot interaction, making him a key figure in the push toward truly perceptive and context-aware machines.