10 citations · 14 across the 10 of their papers we have counts for
10 papers
Beyond Pure Sampling: Hybrid Optimization Mechanisms for Non-Convex Model Predictive Control
Yuichiro Aoyama, Minchan Jung, Akash Ratheesh +1
This paper investigates the optimization mechanisms of non-convex Model Predictive Control (MPC) using the Maximum Entropy Differential Dynamic Programming (ME-DDP) framework. Navi…
Second-Order Stein Variational Dynamic Optimization
Yuichiro Aoyama, Peter Lehmamnn, Evangelos A. Theodorou
We present a novel second-order trajectory optimization algorithm based on Stein Variational Newton's Method and Maximum Entropy Differential Dynamic Programming. The proposed algo…
Second-Order Constrained Dynamic Optimization
Yuichiro Aoyama, Oswin So, Augustinos D. Saravanos +1
This paper provides an overview, analysis, and comparison of second-order dynamic optimization algorithms, i.e., constrained Differential Dynamic Programming (DDP) and Sequential Q…
Generalized Maximum Entropy Differential Dynamic Programming
Yuichiro Aoyama, Evangelos A. Theodorou
We present a sampling-based trajectory optimization method derived from the maximum entropy formulation of Differential Dynamic Programming with Tsallis entropy. This method is a g…
Optimal Control of Granular Material
Yuichiro Aoyama, Amin Haeri, Evangelos A. Theodorou
The control of granular materials, showing up in many industrial applications, is a challenging open research problem. Granular material systems are complex-behavior (as they could…
Gaussian Process Barrier States for Safe Trajectory Optimization and Control
Hassan Almubarak, Manan Gandhi, Yuichiro Aoyama +2
This paper proposes embedded Gaussian Process Barrier States (GP-BaS), a methodology to safely control unmodeled dynamics of nonlinear system using Bayesian learning. Gaussian Proc…
Distributed Differential Dynamic Programming Architectures for Large-Scale Multi-Agent Control
Augustinos D. Saravanos, Yuichiro Aoyama, Hongchang Zhu +1
In this paper, we propose two novel decentralized optimization frameworks for multi-agent nonlinear optimal control problems in robotics. The aim of this work is to suggest archite…
Safety in Augmented Importance Sampling: Performance Bounds for Robust MPPI
Manan Gandhi, Hassan Almubarak, Yuichiro Aoyama +1
This work explores the nature of augmented importance sampling in safety-constrained model predictive control problems. When operating in a constrained environment, sampling based…
Receding Horizon Differential Dynamic Programming Under Parametric Uncertainty
Yuichiro Aoyama, Augustinos D. Saravanos, Evangelos A. Theodorou
Generalized Polynomial Chaos (gPC) theory has been widely used for representing parametric uncertainty in a system, thanks to its ability to propagate uncertainty evolution. In an…
Constrained Differential Dynamic Programming Revisited
Yuichiro Aoyama, George Boutselis, Akash Patel +1
Differential Dynamic Programming (DDP) has become a well established method for unconstrained trajectory optimization. Despite its several applications in robotics and controls how…