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 …

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

This work establishes COMPRA, a compact and reactive autonomy framework for fast
deployment of Micro Aerial Vehicles (MAVs) in subterranean Search-and-Rescue (SAR) …

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 …

In the control systems community, path-following refers to the problem of tracking an output
reference curve. This work presents a novel model predictive path-following control …

We present a case study applying learning-based distributionally robust model predictive
control to highway motion planning under stochastic uncertainty of the lane change behavior …

We consider the problem of interaction-aware motion planning for automated vehicles in
general traffic situations. We model the interaction between the controlled vehicle and …

In this paper, we investigate trajectory tracking and obstacle avoidance for a nonholonomic
system subject to external disturbances by a nonlinear switched model predictive control …

In this article, we propose a reactive constrained navigation scheme, with embedded
obstacles avoidance for an unmanned aerial vehicle (UAV), for enabling navigation in …

Abstract Micro Aerial Vehicles (MAVs) navigation in subterranean environments is gaining
attention in the field of aerial robotics, however there are still multiple challenges for collision …