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Found 4 papers, 1 papers with code
Coriolis Factorizations and their Connections to Riemannian Geometry
Many energy-based control strategies for mechanical systems require the choice of a Coriolis factorization satisfying a skew-symmetry property.
CACTO: Continuous Actor-Critic with Trajectory Optimization -- Towards global optimality
Thus, our algorithm learns a "good" control policy via TO-guided RL policy search that, when used as initial guess provider for TO, makes the trajectory optimization process less prone to converge to poor local optima.
Generalization in Supervised Learning Through Riemannian Contraction
We prove that Riemannian contraction in a supervised learning setting implies generalization.
A Geometric Characterization of Observability in Inertial Parameter Identification
This paper presents an algorithm to geometrically characterize inertial parameter identifiability for an articulated robot.
Robotics
