Related papers: Obstacle Detection Quality as a Problem-Oriented A…
Detecting traversable road areas ahead a moving vehicle is a key process for modern autonomous driving systems. A common approach to road detection consists of exploiting color features to classify pixels as road or background. These…
This work presents the development of a lane detection system aimed at assisting the driving of conventional and autonomous vehicles. The system was implemented using traditional computer vision techniques, focusing on robustness and…
Automatic detection of traffic accidents is an important emerging topic in traffic monitoring systems. Nowadays many urban intersections are equipped with surveillance cameras connected to traffic management systems. Therefore, computer…
A challenge still to be overcome in the field of visual perception for vehicle and robotic navigation on heavily damaged and unpaved roads is the task of reliable path and obstacle detection. The vast majority of the researches have as…
The condition assessment of road surfaces is essential to ensure their serviceability while still providing maximum road traffic safety. This paper presents a robust stereo vision system embedded in an unmanned aerial vehicle (UAV). The…
This paper presents an artificial evolutionbased method for stereo image analysis and its application to real-time obstacle detection and avoidance for a mobile robot. It uses the Parisian approach, which consists here in splitting the…
For intelligent vehicles, sensing the 3D environment is the first but crucial step. In this paper, we build a real-time advanced driver assistance system based on a low-power mobile platform. The system is a real-time multi-scheme…
The main aim of this work is the development of a vision-based road detection system fast enough to cope with the difficult real-time constraints imposed by moving vehicle applications. The hardware platform, a special-purpose massively…
Lane detection is very important for self-driving vehicles. In recent years, computer stereo vision has been prevalently used to enhance the accuracy of the lane detection systems. This paper mainly presents a multiple lane detection…
Vision-based road detection is an essential functionality for supporting advanced driver assistance systems (ADAS) such as road following and vehicle and pedestrian detection. The major challenges of road detection are dealing with shadows…
In this paper, an stereo-based traversability analysis approach for all terrains in off-road mobile robotics, e.g. Unmanned Ground Vehicles (UGVs) is proposed. This approach reformulates the problem of terrain traversability analysis into…
In this paper, we address the problem of vision-based obstacle avoidance for robotic manipulators. This topic poses challenges for both perception and motion generation. While most work in the field aims at improving one of those aspects,…
Cameras play a crucial role in modern driver assistance systems and are an essential part of the sensor technology for automated driving. The quality of images captured by in-vehicle cameras highly influences the performance of visual…
The current research interest in autonomous driving is growing at a rapid pace, attracting great investments from both the academic and corporate sectors. In order for vehicles to be fully autonomous, it is imperative that the driver…
Road surface reconstruction plays a crucial role in autonomous driving, providing essential information for safe and smooth navigation. This paper enhances the RoadBEV [1] framework for real-time inference on edge devices by optimizing both…
Perception of obstacles remains a critical safety concern for autonomous vehicles. Real-world collisions have shown that the autonomy faults leading to fatal collisions originate from obstacle existence detection. Open source autonomous…
Accurate automated detection of road pavement distresses is critical for the timely identification and repair of potentially accident-inducing road hazards such as potholes and other surface-level asphalt cracks. Deployment of such a system…
We present a novel stereo vision algorithm that is capable of obstacle detection on a mobile-CPU processor at 120 frames per second. Our system performs a subset of standard block-matching stereo processing, searching only for obstacles at…
The detection of unknown traffic obstacles is vital to ensure safe autonomous driving. The standard object-detection methods cannot identify unknown objects that are not included under predefined categories. This is because object-detection…
Precise and prompt identification of road surface conditions enables vehicles to adjust their actions, like changing speed or using specific traction control techniques, to lower the chance of accidents and potential danger to drivers and…