Radar overcomes the shortcomings of laser, stereovision, and sonar because it can operate successfully in dusty, foggy, blizzard-blinding, and poorly lit scenarios. This paper presents a novel method for ground and obstacle segmentation based on radar sensing. The algorithm operates directly in the sensor frame, without the need for a separate synchronised navigation source, calibration parameters describing the location of the radar in the vehicle frame, or the geometric restrictions made in the previous main method in the field. Experimental results are presented in various urban scenarios to validate this approach, showing its potential applicability for advanced driving assistance systems and autonomous vehicle operations
This paper presents a radar-vision classification approach to segment the visual scene into ground a...
Mid-air, near mid-air, and on-ground collisions are among the main causes of accident in general avi...
The views and conclusions expressed in this document are those of the author and should not be inter...
Radar overcomes the shortcomings of laser, stereovision, and sonar because it can operate successful...
Ground segmentation is critical for a mobile robot to successfully accomplish its tasks in challengi...
Imaging sensors are being increasingly used in autonomous vehicle applications for scene understandi...
This thesis covers the development of an imaging radar capable of detecting hidden obstacles for ter...
Autonomous unmanned aerial systems (UAS) are having an increasing impact in the scientific community...
Autonomous vehicle operations in outdoor environments challenge robotic perception. Construction, mi...
Unmanned aerial systems (UASs) have enormous potential in many fields of application, especially whe...
In last years the interest in transportation security has increased significantly, in particular wit...
This thesis addresses the problem of object detection with automotive radar sensors in the field of ...
Autonomous vehicles operating in on-road environments need to be aware of the presence and motion of...
Deployment of automated ground vehicles (AGVs) beyond the confines of sunny and dry climes will requ...
For mobile robots operating in outdoor environments, per- ception is a critical task. Construction, ...
This paper presents a radar-vision classification approach to segment the visual scene into ground a...
Mid-air, near mid-air, and on-ground collisions are among the main causes of accident in general avi...
The views and conclusions expressed in this document are those of the author and should not be inter...
Radar overcomes the shortcomings of laser, stereovision, and sonar because it can operate successful...
Ground segmentation is critical for a mobile robot to successfully accomplish its tasks in challengi...
Imaging sensors are being increasingly used in autonomous vehicle applications for scene understandi...
This thesis covers the development of an imaging radar capable of detecting hidden obstacles for ter...
Autonomous unmanned aerial systems (UAS) are having an increasing impact in the scientific community...
Autonomous vehicle operations in outdoor environments challenge robotic perception. Construction, mi...
Unmanned aerial systems (UASs) have enormous potential in many fields of application, especially whe...
In last years the interest in transportation security has increased significantly, in particular wit...
This thesis addresses the problem of object detection with automotive radar sensors in the field of ...
Autonomous vehicles operating in on-road environments need to be aware of the presence and motion of...
Deployment of automated ground vehicles (AGVs) beyond the confines of sunny and dry climes will requ...
For mobile robots operating in outdoor environments, per- ception is a critical task. Construction, ...
This paper presents a radar-vision classification approach to segment the visual scene into ground a...
Mid-air, near mid-air, and on-ground collisions are among the main causes of accident in general avi...
The views and conclusions expressed in this document are those of the author and should not be inter...