Over the past decades, the advantages of optimization-based control techniques over
conventional controllers inspired developments that enabled the use of model predictive …

This letter proposes a Novel Nonlinear Model Predictive Control (NMPC) for navigation and
obstacle avoidance of an Unmanned Aerial Vehicle (UAV). The proposed NMPC formulation …

Unmanned Aerial Vehicles have undergone rapid developments in recent decades. This
has made them very popular for various military and civilian applications allowing us to …

Abstract We present Optimization Engine (OpEn): an open-source code generation
framework for real-time embedded nonconvex optimization, which implements a novel …

We employ the proximal averaged Newton-type method for optimal control (PANOC) to
solve obstacle avoidance problems in real time. We introduce a novel modeling framework …

We present successive convexification, a real-time-capable solution method for nonconvex
trajectory optimization, with continuous-time constraint satisfaction and guaranteed …

We investigate finite-dimensional constrained structured optimization problems, featuring
composite objective functions and set-membership constraints. Offering an expressive yet …

Composite optimization offers a powerful modeling tool for a variety of applications and is
often numerically solved by means of proximal gradient methods. In this paper, we consider …

In this paper, we present an online nonlinear Model Predictive Control (MPC) method for
collision-free, deadlock-free navigation by multiple autonomous nonholonomic Wheeled …

We propose a methodology for autonomous aerial navigation and obstacle avoidance of
micro aerial vehicles (MAVs) using non-linear model predictive control (NMPC) and we …