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Gaussian Process Barrier States for Safe Trajectory Optimization and Control
We derive the barrier state dynamics utilizing the GP posterior, which is used to construct a safety embedded Gaussian process dynamical model (GPDM).
Distributed Differential Dynamic Programming Architectures for Large-Scale Multi-Agent Control
The aim of this work is to suggest architectures that inherit the computational efficiency and scalability of Differential Dynamic Programming (DDP) and the distributed nature of the Alternating Direction Method of Multipliers (ADMM).
Safety in Augmented Importance Sampling: Performance Bounds for Robust MPPI
This work explores the nature of augmented importance sampling in safety-constrained model predictive control problems.
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