2018 Second IEEE International Conference on Robotic Computing (IRC)最新文献

Learning a Set of Interrelated Tasks by Using Sequences of Motor Policies for a Strategic Intrinsically Motivated Learner 策略性内在动机学习者使用动作策略序列学习一组相互关联的任务

2018 Second IEEE International Conference on Robotic Computing (IRC) Pub Date : 2018-10-11 DOI: 10.1109/IRC.2018.00061

Nicolas Duminy, S. Nguyen, D. Duhaut

{"title":"Learning a Set of Interrelated Tasks by Using Sequences of Motor Policies for a Strategic Intrinsically Motivated Learner","authors":"Nicolas Duminy, S. Nguyen, D. Duhaut","doi":"10.1109/IRC.2018.00061","DOIUrl":"https://doi.org/10.1109/IRC.2018.00061","url":null,"abstract":"We propose an active learning architecture for robots, capable of organizing its learning process to achieve a field of complex tasks by learning sequences of motor policies, called Intrinsically Motivated Procedure Babbling (IM-PB). The learner can generalize over its experience to continuously learn new tasks. It chooses actively what and how to learn based by empirical measures of its own progress. In this paper, we are considering the learning of a set of interrelated tasks outcomes hierarchically organized. We introduce a framework called \"\"procedures\", which are sequences of policies defined by the combination of previously learned skills. Our algorithmic architecture uses the procedures to autonomously discover how to combine simple skills to achieve complex goals. It actively chooses between 2 strategies of goal-directed exploration: exploration of the policy space or the procedural space. We show on a simulated environment that our new architecture is capable of tackling the learning of complex motor policies, to adapt the complexity of its policies to the task at hand. We also show that our \"\"procedures\"\" framework helps the learner to tackle difficult hierarchical tasks.","PeriodicalId":416113,"journal":{"name":"2018 Second IEEE International Conference on Robotic Computing (IRC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123741921","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: 8

Improving Code Quality in ROS Packages Using a Temporal Extension of First-Order Logic 利用一阶逻辑的时间扩展提高ROS包的代码质量

2018 Second IEEE International Conference on Robotic Computing (IRC) Pub Date : 2018-06-01 DOI: 10.1109/IRC.2018.00010

D. Come, Julien Brunel, D. Doose

引用次数: 6

Rapid Qualification of Mereotopological Relationships Using Signed Distance Fields 利用符号距离域快速确定微拓扑关系

2018 Second IEEE International Conference on Robotic Computing (IRC) Pub Date : 2018-06-01 DOI: 10.1109/IRC.2018.00031

R. Schubotz, Christian Vogelgesang, D. Rubinstein

引用次数: 0

Towards a Multi-mission QoS and Energy Manager for Autonomous Mobile Robots 面向自主移动机器人的多任务QoS和能量管理

2018 Second IEEE International Conference on Robotic Computing (IRC) Pub Date : 2018-04-05 DOI: 10.1109/IRC.2018.00057

Dinh-Khanh Ho, K. B. Chehida, Benoît Miramond, M. Auguin

引用次数: 6

A Computational Framework for Complementary Situational Awareness (CSA) in Surgical Assistant Robots 手术辅助机器人互补态势感知(CSA)计算框架

2018 Second IEEE International Conference on Robotic Computing (IRC) Pub Date : 2018-04-02 DOI: 10.1109/IRC.2018.00011

Preetham Chalasani, A. Deguet, P. Kazanzides, R. Taylor

{"title":"A Computational Framework for Complementary Situational Awareness (CSA) in Surgical Assistant Robots","authors":"Preetham Chalasani, A. Deguet, P. Kazanzides, R. Taylor","doi":"10.1109/IRC.2018.00011","DOIUrl":"https://doi.org/10.1109/IRC.2018.00011","url":null,"abstract":"Robotic surgical systems have contributed greatly to the advancement of minimally invasive surgery (MIS). More specifically, telesurgical robots have provided enhanced dexterity to surgeons performing MIS procedures. However, current robotic teleoperated systems have only limited situational awareness of the patient anatomy and surgical environment that would typically be available to a surgeon in an open surgery. Although the endoscopic view enhances the visualization of the anatomy, perceptual understanding of the environment and anatomy is still lacking due to the absence of sensory feedback. To address these limitations, we present an algorithmic software framework to provide Complementary Situational Awareness (CSA) in a surgical assistant. This framework aims at improving the human-robot relationship by providing elaborate guidance and sensory feedback capabilities for the surgeon in complex MIS procedures. Unlike traditional teleoperation, this framework enables the user to telemanipulate the situational model in a virtual environment and uses that information to command the slave robot with appropriate admittance gains and environmental constraints. Simultaneously, the situational model is updated based on interaction of the slave robot with the task space environment. We provide various high-level and mid-level components to provide CSA and illustrate the necessary capabilities required for any robotic platform to readily incorporate CSA. We also demonstrate the use of our framework for constrained model-mediated teleoperation using the open-source da Vinci Research Kit (dVRK) hardware.","PeriodicalId":416113,"journal":{"name":"2018 Second IEEE International Conference on Robotic Computing (IRC)","volume":"138 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127336960","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: 11

Locomoting Robots Composed of Immobile Robots 由不能移动的机器人组成的运动机器人

2018 Second IEEE International Conference on Robotic Computing (IRC) Pub Date : 2018-02-14 DOI: 10.1109/IRC.2018.00047

Ross Warkentin, W. Savoie, D. Goldman

引用次数: 3

Reliable Navigation Planning Implementation on a Two-Wheeled Mobile Robot 两轮移动机器人的可靠导航规划实现

2018 Second IEEE International Conference on Robotic Computing (IRC) Pub Date : 2018-01-31 DOI: 10.1109/IRC.2018.00035

Élise Crepon, A. Panchea, Alexandre Chapoutot

引用次数: 4

System Design for Coordinated Multi-robot Assistance Deployment in Smart Spaces 智能空间多机器人协同辅助部署系统设计

2018 Second IEEE International Conference on Robotic Computing (IRC) Pub Date : 2018-01-31 DOI: 10.1109/IRC.2018.00068

P. Papadakis, Christopher Lohr, Marin Lujak, Abir-Beatrice Karami, I. Kanellos, G. Lozenguez, A. Fleury

引用次数: 5

A Co-design Approach for a Rehabilitation Robot Coach for Physical Rehabilitation Based on the Error Classification of Motion Errors 基于运动误差分类的康复机器人教练协同设计方法

2018 Second IEEE International Conference on Robotic Computing (IRC) Pub Date : 2018-01-31 DOI: 10.1109/IRC.2018.00074

M. Devanne, S. Nguyen, O. Rémy-Néris, Beatrice Le Gales-Garnett, G. Kermarrec, A. Thépaut

{"title":"A Co-design Approach for a Rehabilitation Robot Coach for Physical Rehabilitation Based on the Error Classification of Motion Errors","authors":"M. Devanne, S. Nguyen, O. Rémy-Néris, Beatrice Le Gales-Garnett, G. Kermarrec, A. Thépaut","doi":"10.1109/IRC.2018.00074","DOIUrl":"https://doi.org/10.1109/IRC.2018.00074","url":null,"abstract":"The rising number of the elderly incurs growing concern about healthcare, and in particular rehabilitation healthcare. Assistive technology and assistive robotics in particular may help to improve this process. We develop a robot coach capable of demonstrating rehabilitation exercises to patients, watch a patient carry out the exercises and give him feedback so as to improve his performance and encourage him. The HRI of the system is based on our study with a team of rehabilitation therapists and with the target population. The system relies on human motion analysis. We develop a method for learning a probabilistic representation of ideal movements from expert demonstrations. A Gaussian Mixture Model is employed from position and orientation features captured using a Microsoft Kinect v2. For assessing patients' movements, we propose a real-time multi-level analysis to both temporally and spatially identify and explain body part errors. This analysis combined with a classification algorithm allows the robot to provide coaching advice to make the patient improve his movements. The evaluation on three rehabilitation exercises shows the potential of the proposed approach for learning and assessing kinaesthetic movements.","PeriodicalId":416113,"journal":{"name":"2018 Second IEEE International Conference on Robotic Computing (IRC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133056542","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: 17

Reliable Motion Plannning for a Mobile Robot 移动机器人的可靠运动规划

2018 Second IEEE International Conference on Robotic Computing (IRC) Pub Date : 2018-01-31 DOI: 10.1109/IRC.2018.00085

Élise Crepon, A. Panchea, Alexandre Chapoutot

引用次数: 2