Convex optimization for trajectory generation: A tutorial on generating dynamically feasible trajectories reliably and efficiently
Reliable and efficient trajectory generation methods are a fundamental need for
autonomous dynamical systems. The goal of this article is to provide a comprehensive …
autonomous dynamical systems. The goal of this article is to provide a comprehensive …
Advances in trajectory optimization for space vehicle control
Abstract Space mission design places a premium on cost and operational efficiency. The
search for new science and life beyond Earth calls for spacecraft that can deliver scientific …
search for new science and life beyond Earth calls for spacecraft that can deliver scientific …
Variations and extension of the convex–concave procedure
T Lipp, S Boyd - Optimization and Engineering, 2016 - Springer
We investigate the convex–concave procedure, a local heuristic that utilizes the tools of
convex optimization to find local optima of difference of convex (DC) programming problems …
convex optimization to find local optima of difference of convex (DC) programming problems …
Convex optimization for trajectory generation
Reliable and efficient trajectory generation methods are a fundamental need for
autonomous dynamical systems of tomorrow. The goal of this article is to provide a …
autonomous dynamical systems of tomorrow. The goal of this article is to provide a …
Grey wolf optimizer and whale optimization algorithm for stochastic inventory management of reusable products in a two-level supply chain
Product reuse and recovery is an efficient tool that helps companies to simultaneously
address economic and environmental dimensions of sustainability. This paper presents a …
address economic and environmental dimensions of sustainability. This paper presents a …
[HTML][HTML] A data-driven model to describe and forecast the dynamics of COVID-19 transmission
This paper proposes a dynamic model to describe and forecast the dynamics of the
coronavirus disease COVID-19 transmission. The model is based on an approach …
coronavirus disease COVID-19 transmission. The model is based on an approach …
Local learning enabled iterative linear quadratic regulator for constrained trajectory planning
Trajectory planning is one of the indispensable and critical components in robotics and
autonomous systems. As an efficient indirect method to deal with the nonlinear system …
autonomous systems. As an efficient indirect method to deal with the nonlinear system …
A machine learning approach to determine the elastic properties of printed fiber-reinforced polymers
This work focuses on the simultaneous determination of the elastic constants and the fiber
orientation state for a short fiber-reinforced polymer composite by performing a minimum of …
orientation state for a short fiber-reinforced polymer composite by performing a minimum of …
A sequential quadratic programming algorithm for nonconvex, nonsmooth constrained optimization
FE Curtis, ML Overton - SIAM Journal on Optimization, 2012 - SIAM
We consider optimization problems with objective and constraint functions that may be
nonconvex and nonsmooth. Problems of this type arise in important applications, many …
nonconvex and nonsmooth. Problems of this type arise in important applications, many …
Adaptive decoupled robust design optimization
Robust design optimization (RDO) is a valuable technique in the design of engineering
structures as it can provide an optimum design solution that is relatively insensitive to input …
structures as it can provide an optimum design solution that is relatively insensitive to input …