39 citations · 86 across the 18 of their papers we have counts for
6 papers · 1 filter
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…
MAV Navigation in Unknown Dark Underground Mines Using Deep Learning
Sina Sharif Mansouri, Christoforos Kanellakis, Petros Karvelis +2
This article proposes a Deep Learning (DL) method to enable fully autonomous flights for low-cost Micro Aerial Vehicles (MAVs) in unknown dark underground mine tunnels. This kind o…
MAV Development Towards Navigation in Unknown and Dark Mining Tunnels
Dariusz Kominiak, Sina Sharif Mansouri, Christoforos Kanellakis +1
The Mining industry considers the deployment of MAV for autonomous inspection of tunnels and shafts to increase safety and productivity. However, mines are challenging and harsh en…