Manuel Ahumada
Papers
1
Total Citations
17
H-Index
1
About
Manuel Ahumada is a leading researcher in mobile robotics, specializing in state estimation, proprioceptive sensing, and disturbance rejection for autonomous systems. His work centers on enabling robots to navigate reliably in challenging, slip-prone environments without relying on external sensors. In his highly cited 2023 paper, "Fully Proprioceptive Slip-Velocity-Aware State Estimation for Mobile Robots via Invariant Kalman Filtering and Disturbance Observer," Ahumada introduced a novel slip estimator that fuses inertial measurement unit data with body velocity using a Right Invariant Extended Kalman Filter and a Disturbance Observer. This breakthrough allows robots to estimate their state and detect wheel slip using only onboard sensors, achieving robust performance where traditional methods fail. With 17 citations in just two years, this work has already influenced the field of field robotics and autonomous navigation. Ahumada’s contributions are pivotal for advancing the reliability of mobile robots in agriculture, mining, and planetary exploration, where external positioning is unavailable. His research exemplifies how theoretical advances in invariant filtering can yield practical, high-impact solutions for real-world robotic autonomy.
Research Focus
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Top Papers
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