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2019 European Conference on Mobile Robots (ECMR)最新文献

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A Submap per Perspective - Selecting Subsets for SuPer Mapping that Afford Superior Localization Quality 每个视角的子地图-为超级映射选择子集，提供卓越的定位质量
2019 European Conference on Mobile Robots (ECMR) Pub Date : 2019-09-01 DOI: 10.1109/ECMR.2019.8870941
Daniel Adolfsson, Stephanie M. Lowry, Martin Magnusson, A. Lilienthal, Henrik Andreasson
{"title":"A Submap per Perspective - Selecting Subsets for SuPer Mapping that Afford Superior Localization Quality","authors":"Daniel Adolfsson, Stephanie M. Lowry, Martin Magnusson, A. Lilienthal, Henrik Andreasson","doi":"10.1109/ECMR.2019.8870941","DOIUrl":"https://doi.org/10.1109/ECMR.2019.8870941","url":null,"abstract":"This paper targets high-precision robot localization. We address a general problem for voxel-based map representations that the expressiveness of the map is fundamentally limited by the resolution since integration of measurements taken from different perspectives introduces imprecisions, and thus reduces localization accuracy. We propose SuPer maps that contain one Submap per Perspective representing a particular view of the environment. For localization, a robot then selects the submap that best explains the environment from its perspective. Our methods serves as an offline refinement step between initial SLAM and deploying autonomous robots for navigation. We evaluate the proposed method on simulated and real-world data that represent an important use case of an industrial scenario with high accuracy requirements in an repetitive environment. Our results demonstrate a significantly improved localization accuracy, up to 46% better compared to localization in global maps, and up to 25% better compared to alternative submapping approaches.","PeriodicalId":435630,"journal":{"name":"2019 European Conference on Mobile Robots (ECMR)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125905248","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: 5
Towards Long-Term Deployment of a Mobile Robot for at-Home Ambient Assisted Living of the Elderly 面向老年人居家环境辅助生活移动机器人的长期部署
2019 European Conference on Mobile Robots (ECMR) Pub Date : 2019-09-01 DOI: 10.1109/ECMR.2019.8870924
M. Luperto, J. Monroy, J. Ruiz-Sarmiento, F. Moreno, Nicola Basilico, Javier González, N. A. Borghese
{"title":"Towards Long-Term Deployment of a Mobile Robot for at-Home Ambient Assisted Living of the Elderly","authors":"M. Luperto, J. Monroy, J. Ruiz-Sarmiento, F. Moreno, Nicola Basilico, Javier González, N. A. Borghese","doi":"10.1109/ECMR.2019.8870924","DOIUrl":"https://doi.org/10.1109/ECMR.2019.8870924","url":null,"abstract":"In a social and economic context characterized by a constantly aging population, the research for new technologies able to assist elderly people is becoming a hot topic. In this paper we illustrate the main components of the European project MoveCare, a multi-actor framework designed to assist pre-frail elders living alone. The main component of the system is an assistance mobile robot that provides the user with a set of functionalities to support cognitive and social stimulation, assistance, and transparent monitoring. In view of the long-term deployment of the autonomous robotic system to be carried out for three months inside the houses of end-users, we present in this paper a preliminary experimental evaluation of the system within an apartment, focusing on the evaluation of the platform under the perspective of long-term autonomy (LTA).","PeriodicalId":435630,"journal":{"name":"2019 European Conference on Mobile Robots (ECMR)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130091441","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: 22
Image Segmentation on Embedded Systems via Superpixel Convolutional Networks 基于超像素卷积网络的嵌入式系统图像分割
2019 European Conference on Mobile Robots (ECMR) Pub Date : 2019-09-01 DOI: 10.1109/ECMR.2019.8870967
S. Mentasti, M. Matteucci
{"title":"Image Segmentation on Embedded Systems via Superpixel Convolutional Networks","authors":"S. Mentasti, M. Matteucci","doi":"10.1109/ECMR.2019.8870967","DOIUrl":"https://doi.org/10.1109/ECMR.2019.8870967","url":null,"abstract":"In this paper we describe a lightweight framework for fast image segmentation on embedded systems, based on superpixels, which leverages on convolutional and graph-convolutional neural networks. In particular, we analyzed different superpixel representation looking for the best tradeoff between the efficiency of the system and richness of the description. Similarly, we analyzed different network sizes, balancing the number of filters used and the prediction accuracy. We also compared two different convolutional architecture, one based on the classical encoder-decoder paradigm and one based on graphs, to guarantee a most accurate representation of the image structure. The architecture was tested on the KITTI dataset using an embedded system with CUDA capabilities.","PeriodicalId":435630,"journal":{"name":"2019 European Conference on Mobile Robots (ECMR)","volume":"214 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133894652","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: 1
Human Motion Prediction Based on Object Interactions 基于物体交互的人体运动预测
2019 European Conference on Mobile Robots (ECMR) Pub Date : 2019-09-01 DOI: 10.1109/ECMR.2019.8870963
Lilli Bruckschen, Nils Dengler, Maren Bennewitz
{"title":"Human Motion Prediction Based on Object Interactions","authors":"Lilli Bruckschen, Nils Dengler, Maren Bennewitz","doi":"10.1109/ECMR.2019.8870963","DOIUrl":"https://doi.org/10.1109/ECMR.2019.8870963","url":null,"abstract":"In this paper, we consider the problem of predicting the navigation goal of a moving human in an indoor environment. Knowledge about this goal can greatly increase the efficiency of robots acting in the same environment as interferences can be avoided and assistance quickly provided if necessary. Often the navigation goal depends on the previous action of the human and the object the human has interacted with before. Thus, the information about previous object interactions can be used to infer possible objects the human will interact with next, which in term can be used to predict the current navigation goal. We propose to learn a probability distribution of subsequent object interactions and present a framework that utilizes the learned transition model as well as observations of the human's location and pose for the prediction of their movement goal. As we show in various experiments, the information about transition probabilities of object interactions leads to reliable predictions of the navigation goal and improves the accuracy compared to prediction approaches that rely only on spatial information and do not consider object interactions. Furthermore, we demonstrate how the prediction can be used to realize foresighted robot navigation.","PeriodicalId":435630,"journal":{"name":"2019 European Conference on Mobile Robots (ECMR)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114772508","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: 7
Traversal Cost Modeling Based on Motion Characterization for Multi-legged Walking Robots 基于运动表征的多足步行机器人遍历代价建模
2019 European Conference on Mobile Robots (ECMR) Pub Date : 2019-09-01 DOI: 10.1109/ECMR.2019.8870912
Miloš Prágr, P. Čížek, J. Faigl
{"title":"Traversal Cost Modeling Based on Motion Characterization for Multi-legged Walking Robots","authors":"Miloš Prágr, P. Čížek, J. Faigl","doi":"10.1109/ECMR.2019.8870912","DOIUrl":"https://doi.org/10.1109/ECMR.2019.8870912","url":null,"abstract":"In this paper, we concern a traversal cost estimation considering motion control of a hexapod walking robot. The proposed idea is motivated by the observation that the traversal cost depends not only on the traversed terrain but also on the robot motion. Based on the experimental deployments, the forward motion is preferable over some terrains; however, uphill and downhill locomotion over the particular terrain might differ significantly. Therefore, we propose to enhance the traversal cost model by a motion characterization. The model is learned using feature descriptor composed of terrain shape and appearance that is combined with the expected motion performance determined from the slope change and possible rotation of the robot. The traversal model enables to reason about the robot stability regarding placement of the robot legs and performed motion action. The proposed idea of motion characterization is demonstrated and experimentally verified on a simplified motion control using grid-based planning with the robot control decomposed into straight and turn movements.","PeriodicalId":435630,"journal":{"name":"2019 European Conference on Mobile Robots (ECMR)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121769101","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: 2
A Sampling-Based Algorithm for Planning Smooth Nonholonomic Paths 一种基于采样的光滑非完整路径规划算法
2019 European Conference on Mobile Robots (ECMR) Pub Date : 2019-09-01 DOI: 10.1109/ECMR.2019.8870949
C. Beretta, C. Brizzolari, Davide Tateo, Alessandro Riva, F. Amigoni
{"title":"A Sampling-Based Algorithm for Planning Smooth Nonholonomic Paths","authors":"C. Beretta, C. Brizzolari, Davide Tateo, Alessandro Riva, F. Amigoni","doi":"10.1109/ECMR.2019.8870949","DOIUrl":"https://doi.org/10.1109/ECMR.2019.8870949","url":null,"abstract":"The ability to navigate in an environment is essential to the autonomy of mobile robots and unmanned autonomous vehicles. Informally, path planning computes a collision-free path from a start location to a goal location in a known environment. Computing such paths accounting for the kinematics of the robot is a problem widely addressed in the literature, often focusing on feasibility and optimality of the planned paths. Although the smoothness of the paths is a major concern in most applications, the widely used sampling-based approaches often produce quirky winding paths. In this paper, we propose a novel path planning algorithm that is able to produce smooth paths, particularly when considering nonholonomic robot kinematics, like the differential drive kinematics. Comparative experiments show the effectiveness of the proposed algorithm in producing smooth paths.","PeriodicalId":435630,"journal":{"name":"2019 European Conference on Mobile Robots (ECMR)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122096308","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: 0
A Loop Shaping Method for Stabilising a Riderless Bicycle 一种稳定无骑手自行车的环形成形方法
2019 European Conference on Mobile Robots (ECMR) Pub Date : 2019-09-01 DOI: 10.1109/ECMR.2019.8870965
Tom Andersson, N. Persson, A. Fattouh, Martin C. Ekström
{"title":"A Loop Shaping Method for Stabilising a Riderless Bicycle","authors":"Tom Andersson, N. Persson, A. Fattouh, Martin C. Ekström","doi":"10.1109/ECMR.2019.8870965","DOIUrl":"https://doi.org/10.1109/ECMR.2019.8870965","url":null,"abstract":"Several control methods have been proposed to stabilise riderless bicycles but they do not have sufficient simplicity for practical applications. This paper proposes a practical approach to model an instrumented bicycle as a combination of connected systems. Using this model, a PID controller is designed by a loop shaping method to stabilise the instrumented riderless bicycle. The initial results show that the bicycle can be stabilised when running on a roller. The work presented in this paper shows that it is possible to self stabilise a riderless bicycle using cascade PI/PID controllers.","PeriodicalId":435630,"journal":{"name":"2019 European Conference on Mobile Robots (ECMR)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125098519","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: 1
Learning Path Tracking for Real Car-like Mobile Robots From Simulation 基于仿真的真实类车移动机器人学习路径跟踪
2019 European Conference on Mobile Robots (ECMR) Pub Date : 2019-09-01 DOI: 10.1109/ECMR.2019.8870947
Danial Kamran, Junyi Zhu, M. Lauer
{"title":"Learning Path Tracking for Real Car-like Mobile Robots From Simulation","authors":"Danial Kamran, Junyi Zhu, M. Lauer","doi":"10.1109/ECMR.2019.8870947","DOIUrl":"https://doi.org/10.1109/ECMR.2019.8870947","url":null,"abstract":"In this paper we propose a Reinforcement Learning (RL) algorithm for path tracking of a real car-like robot. The RL network is trained in simulation and then evaluated on a small racing car without modification. We provide a big number of training data during off-line simulation using a random path generator to cover different curvatures and initial positions, headings and velocities of the vehicle for the RL agent. Comparing to similar RL based algorithms, we utilize Convolutional Neural Network (CNN) as image embedder for estimating useful information about current and future position of the vehicle relative to the path. Evaluations for running the trained agent on the real car show that the RL agent can control the car smoothly and reduce the velocity adaptively to follow a sample track. We also compared the proposed approach with a conventional lateral controller and results show smoother maneuvers and smaller cross-track errors for the proposed algorithm.","PeriodicalId":435630,"journal":{"name":"2019 European Conference on Mobile Robots (ECMR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129986486","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: 16
Boat Hunting with Semantic Segmentation for Flexible and Autonomous Manufacturing 基于语义分割的柔性自主制造寻船方法
2019 European Conference on Mobile Robots (ECMR) Pub Date : 2019-09-01 DOI: 10.1109/ECMR.2019.8870921
Matteo Terreran, Morris Antonello, S. Ghidoni
{"title":"Boat Hunting with Semantic Segmentation for Flexible and Autonomous Manufacturing","authors":"Matteo Terreran, Morris Antonello, S. Ghidoni","doi":"10.1109/ECMR.2019.8870921","DOIUrl":"https://doi.org/10.1109/ECMR.2019.8870921","url":null,"abstract":"Customized mass production of boats and other vehicles requires highly complex manufacturing processes that need a high amount of automation. To enhance the efficiency of such systems, sensing is of paramount importance to provide robots with detailed information about the working environment. In this paper, we propose the use of semantic segmentation to detect the key elements involved in production, to boost automation in the production process. Our main focus is on the sanding process of these tools by means of a robot. We demonstrate the potential of these techniques in an industrial environment featuring a lower degree of variability with respect to the domestic scenes typically considered in the literature. In the production environment, however, higher performances are required to address challenging manufacturing operations successfully. In this work, we also show that exploiting contextual cues and multiple points of view can further boost the reliability of our system, which provides useful data to the other robot modules in charge of navigation, work station recognition, and other tasks. All the methods have been thoroughly validated on the IASLAB RGB-D COROMA Dataset, that was created on purpose. It consists of 46589 RGB-D frames, whose annotation was speeded up thanks to our optimized annotation pipeline.","PeriodicalId":435630,"journal":{"name":"2019 European Conference on Mobile Robots (ECMR)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129542308","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: 4
OnboardDepth: Depth Prediction for Onboard Systems 车载深度:车载系统的深度预测
2019 European Conference on Mobile Robots (ECMR) Pub Date : 2019-09-01 DOI: 10.1109/ECMR.2019.8870943
A. Angelova, Devesh Yamparala, Justin Vincent, C. Leger
{"title":"OnboardDepth: Depth Prediction for Onboard Systems","authors":"A. Angelova, Devesh Yamparala, Justin Vincent, C. Leger","doi":"10.1109/ECMR.2019.8870943","DOIUrl":"https://doi.org/10.1109/ECMR.2019.8870943","url":null,"abstract":"Depth sensing is important for robotics systems for both navigation and manipulation tasks. We here present a learning-based system which predicts accurate scene depth and can take advantage of many types of sensor supervision. We develop an algorithm which combines both supervised and unsupervised constraints to produce high quality depth and which is robust to the presence of noise, sparse sensing, and missing information. Our system is running onboard in realtime, is easy to deploy, and is applicable to a variety of robot platforms.","PeriodicalId":435630,"journal":{"name":"2019 European Conference on Mobile Robots (ECMR)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124567341","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: 2
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