2020 Fourth IEEE International Conference on Robotic Computing (IRC)最新文献_第2页

Informative Mobile Robot Exploration for Radiation Source Localization with a Particle Filter 基于粒子滤波的信息移动机器人辐射源定位

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00024

Nantawat Pinkam, A. Elibol, N. Chong

{"title":"Informative Mobile Robot Exploration for Radiation Source Localization with a Particle Filter","authors":"Nantawat Pinkam, A. Elibol, N. Chong","doi":"10.1109/IRC.2020.00024","DOIUrl":"https://doi.org/10.1109/IRC.2020.00024","url":null,"abstract":"In this work, we consider the localization problem of an unknown radiation source with measurement uncertainty by using robotic systems in a geometric environment. We proposed the scheme for localization of a radioactive source using the particle filter with information gain-based exploration. The traditional method to localize the radiation is to use the gradient descent algorithm. However, such the algorithm may fail to work in the case of uncertain measurements, which lead to an inaccurate outcome. On the other hand, a standard particle filter can be used to deal with the measurement uncertainty, but the estimated intensity result may be unstable since it only uses the current measurement update as a likelihood function. To solve the problem of measurement uncertainty and unstable intensity result, we proposed an exploration method using the information gain with particle filter. The algorithm takes the information of the particles in the filter to estimate the possible actions for the robot. The expected information gain from those actions can be used to select the best possible action for the robot. The proposed method has been verified by the simulations. The proposed strategy can decrease the time it takes to finish the task comparing to the conventional methods such as the lawn mowing algorithm and source estimation seeking algorithm.","PeriodicalId":232817,"journal":{"name":"2020 Fourth IEEE International Conference on Robotic Computing (IRC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129080446","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

Semi-automatic Collection of Marine Debris by Collaborating UAV and UUV 无人机与无人潜航器协同半自动收集海洋垃圾

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00072

N. Shirakura, Takuya Kiyokawa, Hikaru Kumamoto, J. Takamatsu, T. Ogasawara

引用次数: 2

Deep residual neural network-based classification of loaded and unloaded UAV images 基于深度残差神经网络的无人机加载与卸载图像分类

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00088

U. Seidaliyeva, Manal Alduraibi, L. Ilipbayeva, N. Smailov

引用次数: 14

Recurrent Neural Networks for Hierarchically Mapping Human-Robot Poses 基于递归神经网络的人机姿态分层映射

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00016

Zainab Al-Qurashi, Brian D. Ziebart

{"title":"Recurrent Neural Networks for Hierarchically Mapping Human-Robot Poses","authors":"Zainab Al-Qurashi, Brian D. Ziebart","doi":"10.1109/IRC.2020.00016","DOIUrl":"https://doi.org/10.1109/IRC.2020.00016","url":null,"abstract":"To perform many critical manipulation tasks successfully, human-robot mimicking systems should not only accurately copy the position of a human hand, but its orientation as well. Deep learning methods trained from pairs of corresponding human and robot poses offer one promising approach for constructing a human-robot mapping to accomplish this. However, ignoring the spatial and temporal structure of this mapping makes learning it less effective. We propose two different hierarchical architectures that leverage the structural and temporal human-robot mapping. We partially separate the robotic manipulator's end-effector position and orientation while considering the mutual coupling effects between them. This divides the main problem-making the robot match the human's hand position and mimic its orientation accurately along an unknown trajectory-into several sub-problems. We address these using different recurrent neural networks (RNNs) with Long-Short Term Memory (LSTM) that we combine and train hierarchically based on the coupling over the aspects of the robot that each controls. We evaluate our proposed architectures using a virtual reality system to track human table tennis motions and compare with single artificial neural network (ANN) and RNN models. We compare the benefits of using deep learning neural networks with and without our architectures and find smaller errors in position and orientation, along with increased flexibility in wrist movement are obtained by our proposed architectures.","PeriodicalId":232817,"journal":{"name":"2020 Fourth IEEE International Conference on Robotic Computing (IRC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121422550","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

Analytical Differentiation of Manipulator Jacobian 机械手雅可比矩阵的解析微分

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00070

M. Song, Miran Lee, Bumjoo Lee, Young-Dae Hong

引用次数: 0

Robot Framework for Anti-Bullying in Saudi Schools 沙特学校反欺凌机器人框架

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00033

H. Elgibreen, Sumayah Almazyad, Shahad Bin Shuail, Miad Al Qahtani, Latifah ALhwiseen

{"title":"Robot Framework for Anti-Bullying in Saudi Schools","authors":"H. Elgibreen, Sumayah Almazyad, Shahad Bin Shuail, Miad Al Qahtani, Latifah ALhwiseen","doi":"10.1109/IRC.2020.00033","DOIUrl":"https://doi.org/10.1109/IRC.2020.00033","url":null,"abstract":"Despite the well-known damages caused by bullying and despite the extensive studies that have been conducted to understand this phenomenon, bullying is still a huge concern around the world. This paper highlights the bullying phenomenon in Saudi public schools and proposes a new robot framework called “SALAM” to reduce the bullying effect and to introduce an early intervention integrated with child education. Two methods of investigation (interviews and questionnaire) were conducted in this paper to understand the SALAM users' needs and the nature of bullying in Saudi public schools. Based on the investigation results, the SALAM framework architecture and design are proposed. Three main levels of interaction - introduction, storytelling, and evaluation - were developed to allow the robot to interact with the children and to evaluate their understanding of a story in Arabic while engaging them through certain movements. The ultimate purpose of this framework is to introduce robotics into anti-bullying programs targeting Arab countries that are still novices when it comes to bullying prevention programs. The preliminary results of using SALAM in this paper showed that the children were able to connect with the robot and moderators found it easy to use. Thus, SALAM can be used to raise the awareness of bullying and to overcome the current challenges of the anti-bullying programs in Saudi schools.","PeriodicalId":232817,"journal":{"name":"2020 Fourth IEEE International Conference on Robotic Computing (IRC)","volume":"15 13","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120946677","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 Deep Regression Model for Safety Control in Visual Servoing Applications 视觉伺服应用中安全控制的深度回归模型

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00063

Lei Shi, C. Copot, S. Vanlanduit

引用次数: 4

Securing Robot-assisted Minimally Invasive Surgery through Perception Complementarities 通过感知互补保护机器人辅助微创手术

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00013

Yun-Hsuan Su, Yana Sosnovskaya, B. Hannaford, Kevin Huang

{"title":"Securing Robot-assisted Minimally Invasive Surgery through Perception Complementarities","authors":"Yun-Hsuan Su, Yana Sosnovskaya, B. Hannaford, Kevin Huang","doi":"10.1109/IRC.2020.00013","DOIUrl":"https://doi.org/10.1109/IRC.2020.00013","url":null,"abstract":"Laparoscopic surgery presents practical benefits over traditional open surgery, including reduced risk of infection, discomfort and recovery time for patients. Introducing robot systems into surgical tasks provides additional enhancements, including improved precision, remote operation, and an intelligent software layer capable of filtering aberrant motion and scaling surgical maneuvers. However, the software interface in telesurgery also lends itself to potential adversarial cyber attacks. Such attacks can negatively effect both surgeon motion commands and sensory information relayed to the operator. To combat cyber attacks on the latter, one method to enhance surgeon feedback through multiple sensory pathways is to incorporate reliable, complementary forms of information across different sensory modes. Built-in partial redundancies or inferences between perceptual channels, or perception complementarities, can be used both to detect and recover from compromised operator feedback. In surgery, haptic sensations are extremely useful for surgeons to prevent undue and unwanted tissue damage from excessive tool-tissue force. Direct force sensing is not yet deployable due to sterilization requirements of the operating room. Instead, combinations of other sensing methods may be relied upon, such as noncontact model-based force estimation. This paper presents the design of a surgical simulator software that can be used for vision-based non-contact force sensing to inform the perception complementarity of vision and force feedback for telesurgery. A brief user study is conducted to verify the efficacy of graphical force feedback from vision-based force estimation, and suggests that vision may effectively complement direct force sensing.","PeriodicalId":232817,"journal":{"name":"2020 Fourth IEEE International Conference on Robotic Computing (IRC)","volume":"447 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116756042","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

Detection of loaded and unloaded UAV using deep neural network 基于深度神经网络的无人机装卸检测

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00093

U. Seidaliyeva, Manal Alduraibi, L. Ilipbayeva, A. Almagambetov

引用次数: 25

Reuse-oriented SLAM Framework using Software Product Lines 使用软件产品线的面向重用的SLAM框架

2020 Fourth IEEE International Conference on Robotic Computing (IRC) Pub Date : 2020-11-01 DOI: 10.1109/IRC.2020.00037

M. Abdelhady, D. Dresscher, J. Broenink

{"title":"Reuse-oriented SLAM Framework using Software Product Lines","authors":"M. Abdelhady, D. Dresscher, J. Broenink","doi":"10.1109/IRC.2020.00037","DOIUrl":"https://doi.org/10.1109/IRC.2020.00037","url":null,"abstract":"Simultaneous Localization and Mapping (SLAM) is a widely investigated problem in robotics. It depicts the process of a robot creating a map of an unknown environment while concurrently estimating its location within the self-created map. In recent years, many solutions have been proposed to the SLAM problem based on numerous approaches such as probabilistic filters or graph optimization. This work recognizes that, with the growing complexity and the active development in the field of SLAM, reuse is becoming an essential quality as researchers often have to solve architectural issues that are secondary to the core of the problem, which leads to sub-optimal realizations in the final SLAM product from the software point of view. Therefore, a component-based framework is introduced that regards reusability as a primary requirement of SLAM software, which highlights the core separable modules and implements them as encapsulated interchangeable components forming a software product line. The reusability of the framework is evaluated according to the reuse-readiness levels criteria and the results show improved modularity and reduction in the development and deployment time and effort.","PeriodicalId":232817,"journal":{"name":"2020 Fourth IEEE International Conference on Robotic Computing (IRC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114560424","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