1,567 research outputs found
Roving vehicle motion control Final report
Roving vehicle motion control for unmanned planetary and lunar exploratio
Measuring traffic lane-changing by converting video into space–time still images
Empirical data is needed in order to extend our knowledge of traffic behavior. Video recordings are used to enrich typical data from loop detectors. In this context, data extraction from videos becomes a challenging task. Setting automatic video processing systems is costly, complex, and the accuracy achieved is usually not enough to improve traffic flow models. In contrast “visual” data extraction by watching the recordings requires extensive human intervention. A semiautomatic video processing methodology to count lane-changing in freeways is proposed. The method allows counting lane changes faster than with the visual procedure without falling into the complexities and errors of full automation. The method is based on converting the video into a set of space–time still images, from where to visually count. This methodology has been tested at several freeway locations near Barcelona (Spain) with good results. A user-friendly implementation of the method is available on http://bit.ly/2yUi08M.Peer ReviewedPostprint (published version
CNN for Very Fast Ground Segmentation in Velodyne LiDAR Data
This paper presents a novel method for ground segmentation in Velodyne point
clouds. We propose an encoding of sparse 3D data from the Velodyne sensor
suitable for training a convolutional neural network (CNN). This general
purpose approach is used for segmentation of the sparse point cloud into ground
and non-ground points. The LiDAR data are represented as a multi-channel 2D
signal where the horizontal axis corresponds to the rotation angle and the
vertical axis the indexes channels (i.e. laser beams). Multiple topologies of
relatively shallow CNNs (i.e. 3-5 convolutional layers) are trained and
evaluated using a manually annotated dataset we prepared. The results show
significant improvement of performance over the state-of-the-art method by
Zhang et al. in terms of speed and also minor improvements in terms of
accuracy.Comment: ICRA 2018 submissio
Evaluation of Student Interpreters Using Voice Recognition and Automatic Grammar Correction
The evaluation and assessment of student interpreters have long been an issue for interpreting programs. The balance between student practice throughput, the time and human cost of assessment, and the quality of feedback is notoriously difficult to achieve. Here we demonstrate a way to rapidly assess student Chinese-to-English interpreting performance using automatic speech recognition and grammar correction software. The assessment results are compared with human graders against a set of criteria for grammar, fidelity, register, and enunciation. The results show that the semiautomatic assessment process is less time-consuming, and can give adequate feedback for enunciation, grammar, and register. Student volunteers were able to maintain engagement over a three-month period with minimal intervention from the instructor, however, interest began to drop over the long term
Human-centred design methods : developing scenarios for robot assisted play informed by user panels and field trials
Original article can be found at: http://www.sciencedirect.com/ Copyright ElsevierThis article describes the user-centred development of play scenarios for robot assisted play, as part of the multidisciplinary IROMEC1 project that develops a novel robotic toy for children with special needs. The project investigates how robotic toys can become social mediators, encouraging children with special needs to discover a range of play styles, from solitary to collaborative play (with peers, carers/teachers, parents, etc.). This article explains the developmental process of constructing relevant play scenarios for children with different special needs. Results are presented from consultation with panel of experts (therapists, teachers, parents) who advised on the play needs for the various target user groups and who helped investigate how robotic toys could be used as a play tool to assist in the children’s development. Examples from experimental investigations are provided which have informed the development of scenarios throughout the design process. We conclude by pointing out the potential benefit of this work to a variety of research projects and applications involving human–robot interactions.Peer reviewe
Aerospace medicine and biology. A continuing bibliography (supplement 231)
This bibliography lists 284 reports, articles, and other documents introduced into the NASA scientific and technical information system in March 1982
Bioinspired Implementation and Assessment of a Remote-Controlled Robot
This research was funded by the Universidad de Las Americas, Direccion General de Investigacion.Daily activities are characterized by an increasing interaction with smart machines that present a certain level of autonomy. However, the intelligence of such electronic devices is not always transparent for the end user. This study is aimed at assessing the quality of the remote control of a mobile robot whether the artefact exhibits a human-like behavior or not. The bioinspired behavior implemented in the robot is the well-described two-thirds power law. The performance of participants who teleoperate the semiautonomous vehicle implementing the biological law is compared to a manual and nonbiological mode of control. The results show that the time required to complete the path and the number of collisions with obstacles are significantly lower in the biological condition than in the two other conditions. Also, the highest percentage of occurrences of curvilinear or smooth trajectories are obtained when the steering is assisted by an integration of the power law in the robot's way of working. This advanced analysis of the performance based on the naturalness of the movement kinematics provides a refined evaluation of the quality of the Human-Machine Interaction (HMI). This finding is consistent with the hypothesis of a relationship between the power law and jerk minimization. In addition, the outcome of this study supports the theory of a CNS origin of the power law. The discussion addresses the implications of the anthropocentric approach to enhance the HMI.publishersversionpublishe
GAN-Based LiDAR Intensity Simulation
Realistic vehicle sensor simulation is an important element in developing
autonomous driving. As physics-based implementations of visual sensors like
LiDAR are complex in practice, data-based approaches promise solutions. Using
pairs of camera images and LiDAR scans from real test drives, GANs can be
trained to translate between them. For this process, we contribute two
additions. First, we exploit the camera images, acquiring segmentation data and
dense depth maps as additional input for training. Second, we test the
performance of the LiDAR simulation by testing how well an object detection
network generalizes between real and synthetic point clouds to enable
evaluation without ground truth point clouds. Combining both, we simulate LiDAR
point clouds and demonstrate their realism
Traffic Light Recognition for Real Scenes Based on Image Processing and Deep Learning
Traffic light recognition in urban environments is crucial for vehicle control. Many studies have been devoted to recognizing traffic lights. However, existing recognition methods still face many challenges in terms of accuracy, runtime and size. This paper presents a novel robust traffic light recognition approach that takes into account these three aspects based on image processing and deep learning. The proposed approach adopts a two-stage architecture, first performing detection and then classification. In the detection, the perspective relationship and the fractal dimension are both considered to dramatically reduce the number of invalid candidate boxes, i.e. region proposals. In the classification, the candidate boxes are classified by SqueezeNet. Finally, the recognized traffic light boxes are reshaped by postprocessing. Compared with several reference models, this approach is significantly competitive in terms of accuracy and runtime. We show that our approach is lightweight, easy to implement, and applicable to smart terminals, mobile devices or embedded devices in practice
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