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Optimal Control (CMU 16-745) 2024 Lecture 21: Legged Robots and How to Walk with QPs
Calibration of Noise Covariance and Kinematics for State Estimation of Legged Robots (ICRA 2026)
Robust, Visual-Inertial State Estimation: from Frame-based to Event-based Cameras
[Presentation] Legged Robot State Estimation with Dynamic Contact Event Information
[ICRA 2023] Probabilistic Contact State Estimation for Legged Robots using Inertial Information
Thesis Defense - Layered Control Architectures: Constructive Theory and Application to Legged Robots
OptiState: State Estimation of Legged Robots
Legged Robot State-Estimation through Combined Forward Kinematic and Preintegrated Contact Factors
Tim Barfoot | Where Can Machine Learning Help Robotic State Estimation | Tartan SLAM Series
STEP: State Estimator for Legged Robots Using a Preintegrated Foot Velocity Factor
Modeling of legged robots
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Last Updated: October 4, 2026
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Accepted for IEEE Transaction on Robotics Title: Invariant Smoother for Efficiently learn the fundamentals of Lecture 21 for Optimal Control and Reinforcement Learning 2024 by Prof. Zac Manchester. Topics: - History of Noise covariance tuning has long been a bottleneck in I will present the main algorithms to achieve robust, 6-DOF, Published paper: ieeexplore.ieee.org/document/10161485 This work has been released as an open-source project at: ... Fueled in part by the imagination of science fiction, every decade since the 1950s has expected Accompanied video for the IEEE International Conference on ICRA 2018 Spotlight Video Interactive Session Wed PM Pod H.8 Authors: Hartley, Ross; Mangelson, Joshua; Gan, Lu; Ghaffari ... Presentation by Tim Barfoot as part of the Tartan SLAM Series. Series overviews and links can be found on our webpage: ... Teacher: Michele Focchi Contact: michele.focchi Website: mfocchi.github.io Slides: ...