CoCo-InEKF learns continuous contact velocity covariances via a neural network to improve invariant EKF state estimation accuracy and consistency for dynamic legged robot motions without requiring ground-truth contact labels.
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cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
ConstrainedMimic integrates operational space control and control barrier functions into RL tracking policies to enforce arbitrary runtime constraints on humanoid kinematics and dynamics while preserving contact modes and tracking goals.
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CoCo-InEKF: State Estimation with Learned Contact Covariances in Dynamic, Contact-Rich Scenarios
CoCo-InEKF learns continuous contact velocity covariances via a neural network to improve invariant EKF state estimation accuracy and consistency for dynamic legged robot motions without requiring ground-truth contact labels.
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Constrained Whole-Body Tracking for Humanoid Robots
ConstrainedMimic integrates operational space control and control barrier functions into RL tracking policies to enforce arbitrary runtime constraints on humanoid kinematics and dynamics while preserving contact modes and tracking goals.