2019 European Conference on Mobile Robots (ECMR)最新文献_第7页

Sensor Aware Lidar Odometry 传感器感知激光雷达里程计

2019 European Conference on Mobile Robots (ECMR) Pub Date : 2019-07-22 DOI: 10.1109/ECMR.2019.8870929

D. Kovalenko, Mikhail Korobkin, Andrey Minin

引用次数: 10

Motion Control for Steerable Wheeled Mobile Manipulation 可操纵轮式移动操作的运动控制

2019 European Conference on Mobile Robots (ECMR) Pub Date : 2019-07-19 DOI: 10.1109/ECMR.2019.8870958

M. Sorour, A. Cherubini, P. Fraisse

引用次数: 6

Stochastic Optimization for Trajectory Planning with Heteroscedastic Gaussian Processes 异方差高斯过程轨迹规划的随机优化

2019 European Conference on Mobile Robots (ECMR) Pub Date : 2019-07-17 DOI: 10.1109/ECMR.2019.8870970

Luka Petrović, Juraj Peršić, Marija Seder, Ivan Marković

引用次数: 7

Stereo Event Lifetime and Disparity Estimation for Dynamic Vision Sensors 动态视觉传感器的立体事件寿命和视差估计

2019 European Conference on Mobile Robots (ECMR) Pub Date : 2019-07-17 DOI: 10.1109/ECMR.2019.8870946

Antea Hadviger, Ivan Marković, I. Petrović

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引用次数: 3

Real-time Vision-based Depth Reconstruction with NVidia Jetson 基于NVidia Jetson的实时视觉深度重建

2019 European Conference on Mobile Robots (ECMR) Pub Date : 2019-07-16 DOI: 10.1109/ECMR.2019.8870936

A. Bokovoy, K. Muravyev, K. Yakovlev

{"title":"Real-time Vision-based Depth Reconstruction with NVidia Jetson","authors":"A. Bokovoy, K. Muravyev, K. Yakovlev","doi":"10.1109/ECMR.2019.8870936","DOIUrl":"https://doi.org/10.1109/ECMR.2019.8870936","url":null,"abstract":"Vision-based depth reconstruction is a challenging problem extensively studied in computer vision but still lacking universal solution. Reconstructing depth from single image is particularly valuable to mobile robotics as it can be embedded to the modern vision-based simultaneous localization and mapping (vSLAM) methods providing them with the metric information needed to construct accurate maps in real scale. Typically, depth reconstruction is done nowadays via fully-convolutional neural networks (FCNNs). In this work we experiment with several FCNN architectures and introduce a few enhancements aimed at increasing both the effectiveness and the efficiency of the inference. We experimentally determine the solution that provides the best performance/accuracy tradeoff and is able to run on NVidia Jetson with the framerates exceeding 16FPS for 320 × 240 input. We also evaluate the suggested models by conducting monocular vSLAM of unknown indoor environment on NVidia Jetson TX2 in real-time. Open-source implementation of the models and the inference node for Robot Operating System (ROS) are available at https://github.com/CnnDepth/tx2_fcnn_node.","PeriodicalId":435630,"journal":{"name":"2019 European Conference on Mobile Robots (ECMR)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133234885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 14

Learning Objectness from Sonar Images for Class-Independent Object Detection 从声纳图像中学习目标进行类无关目标检测

2019 European Conference on Mobile Robots (ECMR) Pub Date : 2019-07-01 DOI: 10.1109/ECMR.2019.8870959

Matias Valdenegro-Toro

引用次数: 6

Joint Vision-Based Navigation, Control and Obstacle Avoidance for UAVs in Dynamic Environments 动态环境下无人机联合视觉导航、控制与避障

2019 European Conference on Mobile Robots (ECMR) Pub Date : 2019-05-03 DOI: 10.1109/ECMR.2019.8870944

Ciro Potena, D. Nardi, A. Pretto

引用次数: 8