Shounak Das

Papers

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About

Shounak Das is a robotics researcher specializing in state estimation, sensor fusion, and autonomous navigation for wheeled and space robotics. His work centers on developing robust algorithms that enable robots to accurately determine their position, velocity, and orientation in challenging environments. Das is best known for his pioneering integration of zero-velocity updates (ZUPT) with GNSS and inertial navigation systems, demonstrating how leveraging zero-velocity information dramatically improves localization accuracy for wheeled robots—a contribution that has garnered 11 citations in his seminal 2021 paper. He also played a key role in the NASA Space Robotics Challenge 2, where his team developed autonomous lunar rover operations, showcasing multirobot coordination for future Moon missions (10 citations). His recent work on robust state estimation methods (2023) further advances the field by addressing real-world sensor noise and failure scenarios. With a growing citation impact, Das’s research bridges theoretical estimation theory and practical deployment, making him a rising figure in autonomous systems. His achievements highlight a commitment to enabling robots to navigate reliably in both terrestrial and extraterrestrial settings.