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 free navigation in such harsh environments. This article proposes a novel baseline solution for collision free navigation with Nonlinear Model Predictive Control (NMPC). In the proposed method, the MAV is considered as a floating object, where the velocities on the x, y axes and the position on altitude are the references for the NMPC to navigate along the tunnel, while the NMPC avoids the collision by considering kinematics of the obstacles based on measurements from a 2D lidar. Moreover, a novel approach for correcting the heading of the MAV towards the center ...
Safe navigation in unknown environments is a challenging task for autonomous Micro Aerial Vehicle (M...
Micro Aerial Vehicles (MAVs) are platforms that received great attention during the last decade. Rec...
This article proposes a novel control architecture using a centralized nonlinear model predictive co...
Using robots to navigate through un-mapped environments, specially man-made infrastructures, for the...
This article establishes a novel Non linear Model Predictive Control (MPC) scheme for the navigation...
This work establishes a robocentric framework around a non-linear Model Predictive Control (NMPC) fo...
This work establishes a novel robocentric Non-linear Model Predictive Control (NMPC) framework for f...
This letter proposes a novel Nonlinear Model Predictive Control (NMPC) framework for Micro Aerial Ve...
In this thesis, I am going to investigate the control, navigation and path planning frame-works forM...
This article proposes a Deep Learning (DL) method to enable fully autonomous flights for low-cost Mi...
The usage of Micro Aerial Vehicles (MAVs) is rapidly emerging in the mining industry to increase ove...
Degraded Subterranean environments are an attractive case for miniature aerial vehicles, since there...
This article proposes a Novel Nonlinear Model Predictive Control (NMPC) for navigation and obstacle ...
This article presents a Convolutional Neural Network (CNN) method to enable autonomous navigation of...
The usage of Micro Aerial Vehicles (MAVs) in different applications is gaining attention, however on...
Safe navigation in unknown environments is a challenging task for autonomous Micro Aerial Vehicle (M...
Micro Aerial Vehicles (MAVs) are platforms that received great attention during the last decade. Rec...
This article proposes a novel control architecture using a centralized nonlinear model predictive co...
Using robots to navigate through un-mapped environments, specially man-made infrastructures, for the...
This article establishes a novel Non linear Model Predictive Control (MPC) scheme for the navigation...
This work establishes a robocentric framework around a non-linear Model Predictive Control (NMPC) fo...
This work establishes a novel robocentric Non-linear Model Predictive Control (NMPC) framework for f...
This letter proposes a novel Nonlinear Model Predictive Control (NMPC) framework for Micro Aerial Ve...
In this thesis, I am going to investigate the control, navigation and path planning frame-works forM...
This article proposes a Deep Learning (DL) method to enable fully autonomous flights for low-cost Mi...
The usage of Micro Aerial Vehicles (MAVs) is rapidly emerging in the mining industry to increase ove...
Degraded Subterranean environments are an attractive case for miniature aerial vehicles, since there...
This article proposes a Novel Nonlinear Model Predictive Control (NMPC) for navigation and obstacle ...
This article presents a Convolutional Neural Network (CNN) method to enable autonomous navigation of...
The usage of Micro Aerial Vehicles (MAVs) in different applications is gaining attention, however on...
Safe navigation in unknown environments is a challenging task for autonomous Micro Aerial Vehicle (M...
Micro Aerial Vehicles (MAVs) are platforms that received great attention during the last decade. Rec...
This article proposes a novel control architecture using a centralized nonlinear model predictive co...