19 citations · 33 across the 6 of their papers we have counts for
10 papers
Collision avoidance for multiple MAVs using fast centralized NMPC
Björn Lindqvist, Sina Sharif Mansouri, Pantelis Sopasakis +1
This article proposes a novel control architecture using a centralized nonlinear model predictive control (CNMPC) scheme for controlling multiple micro aerial vehicles (MAVs). The…
Geometry Aware NMPC Scheme for Morphing Quadrotor Navigation in Restricted Entrances
Andreas Papadimitriou, Sina Sharif Mansouri, Christoforos Kanellakis +1
Geometry-morphing Micro Aerial Vehicles (MAVs) are gaining more and more attention lately, since their ability to modify their geometric morphology in-flight increases their versat…
Nonlinear MPC for Collision Avoidance and Controlof UAVs With Dynamic Obstacles
Björn Lindqvist, Sina Sharif Mansouri, Ali-akbar Agha-mohammadi +1
This article proposes a Novel Nonlinear Model Predictive Control (NMPC) for navigation and obstacle avoidance of an Unmanned Aerial Vehicle (UAV). The proposed NMPC formulation all…
A Unified NMPC Scheme for MAVs Navigation with 3D Collision Avoidance under Position Uncertainty
Sina Sharif Mansouri, Christoforos Kanellakis, Bjorn Lindqvist +4
This article proposes a novel Nonlinear Model Predictive Control (NMPC) framework for Micro Aerial Vehicle (MAV) autonomous navigation in constrained environments. The introduced f…
Subterranean MAV Navigation based on Nonlinear MPC with Collision Avoidance Constraints
Sina Sharif Mansouri, Christoforos Kanellakis, Emil Fresk +5
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…
Unsupervised Learning for Subterranean Junction Recognition Based on 2D Point Cloud
Sina Sharif Mansouri, Farhad Pourkamali-Anaraki, Miguel Castano Arranz +3
This article proposes a novel unsupervised learning framework for detecting the number of tunnel junctions in subterranean environments based on acquired 2D point clouds. The imple…