Papers
5
Total Citations
199
H-Index
4
About
Dinesh Atchuthan is a robotics researcher whose work focuses on state estimation, legged locomotion, and sensor fusion for complex environments. His most influential contribution is "A micro Lie theory for state estimation in robotics" (2018), which has garnered 158 citations—making it his most-cited work. This paper bridges classical Lie group mathematics with modern robotic estimation, providing a rigorous yet practical framework that has become a foundational reference for researchers working on localization and mapping problems. Atchuthan has also made significant strides in multi-contact locomotion through the Loco3D project, addressing the challenge of enabling legged robots to navigate complex, uneven terrains. His development of WOLF, a modular C++ estimation framework based on factor graphs, offers the robotics community a flexible tool for sensor fusion and state estimation. Additionally, his work on absolute humanoid localization using IMU Lie groups and fiducial markers tackles the critical problem of accurate indoor positioning for legged robots. Through these contributions, Atchuthan has advanced both the theoretical foundations and practical implementations of robotic state estimation, particularly for legged systems operating in challenging environments.
Research Focus
Key Achievements
Top Papers
- 1A micro Lie theory for state estimation in robotics158 citations · 2018
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- 3WOLF: A Modular Estimation Framework for Robotics Based on Factor Graphs13 citations · 2022
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