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This paper presents an efficient navigation system which presents the navigation information to the visually impaired via Kinect and vibrotactile belt. The system consists of three parts. The first part is Kinect, which is used for obstacles detection. The second part is a laptop, the laptop processes the depth data of the context acquired by the Kinect, and then translates safe guidance hint into...
This paper proposes a global navigation strategy for autonomous vehicle combining sensor based control and digital maps information. In order to avoid localization problems in urban environments, this approach intends to solve the global navigation focusing on two local navigation tasks: road lane following and road intersection maneuvers. For that, it is important to use digital maps, once they provide...
Map application has played a more and more important role in today's autonomous drive and navigation techniques. However, most of the existing maps can only reach road-level (meter scale) accuracy, which cannot meet the needs of driving with no hands. Based on this situation, a method to generate lane-level (centimeter scale) orthophoto maps is proposed. This method utilizes a multiple onboard cameras...
This paper presents a novel scheme for Vanishing Points (VPs) estimation and lanes identification through monocular images of mobile robots. VPs detection based on probable vanishing direction hypothesizes and Bayesian posterior probability verification in image Hough space is a foremost contribution. VPs estimation is an optimal resolution based on a weighted objective function. The selected linear...
A new robust lane marking detection algorithm for monocular vision is proposed. It is designed for the urban roads with disturbances and with the weak lane markings. The primary contribution of the paper is that it supplies a robust adaptive method of image segmentation, which employs jointly prior knowledge, statistical information and the special geometrical features of lane markings in the bird's-eye...
Simultaneous localization and mapping, drivability classification of the terrain and path planning represent three major research areas in the field of autonomous outdoor robotics. Especially unstructured environments require a careful examination as they are unknown, continuous and the number of possible actions for the robot are infinite. We present an approach to create a semantic 3D map with drivability...
According to the distribution characteristics of lidar collection points, dense in the vicinity and sparse in the distance, a terrain classification method based on variable-scale three-dimensional grid map is proposed to classify an unknown terrain into four categories, which includes roads, lawns, buildings and trees. First, we establish a variable-scale three-dimensional grid map. Then the algorithm...
In this paper, it discusses the state-of-art of the assistant safety driving technologies. It mainly includes the lane departure warning, ambient vehicle detection and vehicle safety distance keeping, pedestrian detection, driver behavior monitoring, vehicle motion control and communication. In the human-vehicle interaction, the large amount of information from all kinds of sensors should be well...
Driving assistance system has a significant influence on driving safety, and we introduce an integrated Forward Collision Warning(FCW) system based on monocular vision. In order to reduce the searching region of original image, lane making is presented to establish the ROI firstly. Secondly, hypotheses are extracted using Haar-like feature and Adaboost classifier. To remove false positive detection...
Quick and accurate understanding of the ambient environment is critical in the development of the intelligent vehicle. As the most important element consisting the ambient environment, road curb detecting is a fundamental and vital work for the development of intelligent vehicle. In this paper, a framework was presented to detect the road quickly and robustly using the velodyne lidar, which provides...
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