2017 18th International Conference on Advanced Robotics (ICAR)最新文献

Safety evaluation method of robot arm considering energy of contact 考虑接触能的机械臂安全评价方法

2017 18th International Conference on Advanced Robotics (ICAR) Pub Date : 2017-08-30 DOI: 10.1109/ICAR.2017.8023646

H. Nakamoto, N. Matsuhira

引用次数: 1

Robotman: A security robot for human-robot interaction 机器人:用于人机交互的安全机器人

2017 18th International Conference on Advanced Robotics (ICAR) Pub Date : 2017-08-30 DOI: 10.1109/ICAR.2017.8023489

Alexander López, Renato Paredes, Diego Quiroz, G. Trovato, F. Cuéllar

引用次数: 18

Questionnaire experiment using networked service robots 基于网络化服务机器人的问卷实验

2017 18th International Conference on Advanced Robotics (ICAR) Pub Date : 2017-08-30 DOI: 10.1109/ICAR.2017.8023643

Takamasa Ikeda, Mirai Shimoyama, N. Matsuhira

引用次数: 0

Model selection for incremental learning of generalizable movement primitives 可推广运动原语增量学习的模型选择

2017 18th International Conference on Advanced Robotics (ICAR) Pub Date : 2017-08-30 DOI: 10.1109/ICAR.2017.8023633

Murtaza Hazara, V. Kyrki

{"title":"Model selection for incremental learning of generalizable movement primitives","authors":"Murtaza Hazara, V. Kyrki","doi":"10.1109/ICAR.2017.8023633","DOIUrl":"https://doi.org/10.1109/ICAR.2017.8023633","url":null,"abstract":"Although motor primitives (MPs) have been studied extensively, much less attention has been devoted to studying their generalization to new situations. To cope with varying conditions, a MP's policy encoding must support generalization over task parameters to avoid learning separate primitives for each condition. Local and linear parameterized models have been proposed to interpolate over task parameters to provide limited generalization. In this paper, we present a global parametric motion primitive which allows generalization beyond local or linear models. Primitives are modelled using a linear basis function model with global non-linear basis functions. Using the global parametric model, we developed an online incremental learning framework for constructing a database of MPs from a single human demonstration. Above all, we propose a model selection method that can choose an optimal model complexity even with few training samples, which makes it suitable for online incremental learning. Experiments with a ball-in-a-cup task with varying string lengths demonstrate that the global parametric approach can successfully extract underlying regularities in a database of MPs leading to enhanced generalization capability of the parametric MPs and increased speed (convergence rate) of learning. Furthermore, it significantly excels over locally weighted regression both in terms of inter- and extrapolation.","PeriodicalId":198633,"journal":{"name":"2017 18th International Conference on Advanced Robotics (ICAR)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116251896","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

Physical edge detection in clothing items for robotic manipulation 用于机器人操作的服装物品的物理边缘检测

2017 18th International Conference on Advanced Robotics (ICAR) Pub Date : 2017-08-30 DOI: 10.1109/ICAR.2017.8023660

Antonio Gabas, Y. Kita

引用次数: 7

Computer vision in remotely piloted aircraft (RPA) to avoid obstacles during flight 远程驾驶飞机(RPA)在飞行过程中避障的计算机视觉

2017 18th International Conference on Advanced Robotics (ICAR) Pub Date : 2017-07-10 DOI: 10.1109/ICAR.2017.8023626

W. M. Martins, A. B. Ramos, R. G. Braga, Luciano do V. Ribeiro, F. Mora-Camino

引用次数: 1

Storing and retrieving perceptual episodic memories for long-term manipulation tasks 长期操作任务中知觉情景记忆的存储和检索

2017 18th International Conference on Advanced Robotics (ICAR) Pub Date : 2017-07-10 DOI: 10.1109/ICAR.2017.8023492

Ferenc Bálint-Benczédi, Zoltán-Csaba Márton, M. Durner, M. Beetz

{"title":"Storing and retrieving perceptual episodic memories for long-term manipulation tasks","authors":"Ferenc Bálint-Benczédi, Zoltán-Csaba Márton, M. Durner, M. Beetz","doi":"10.1109/ICAR.2017.8023492","DOIUrl":"https://doi.org/10.1109/ICAR.2017.8023492","url":null,"abstract":"With recent technological advances, robotic agents are increasingly capable of performing ever more sophisticated manipulation tasks. Perceptual capabilities of these robots need to be able to adapt to the wide variety of tasks they are to perform. Remembering what a robot has seen, what the rationale was behind the decisions it took or how it ended up understanding the world as it did, are important questions if we want perception capabilities that can scale towards real-world manipulation. We present a robotic perception system that generates perceptual episodic memories during the execution of a task. To allow easy retrieval of these memories we introduce an object and scene description language that serves as a layer of abstraction between the structure of the perception logs and the semantic interpretation of these. The description language can be used through a query interface to retrieve specific parts of the generated episodic memory. The purpose of the proposed system is two-fold: to enable on-line retrospection and specialized training of perception routines and to enable researchers to interactively explore perception results.","PeriodicalId":198633,"journal":{"name":"2017 18th International Conference on Advanced Robotics (ICAR)","volume":"243 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123026411","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

Nonlinear optimal control for autonomous navigation of a truck and trailer system 卡车和拖车系统自主导航的非线性最优控制

2017 18th International Conference on Advanced Robotics (ICAR) Pub Date : 2017-07-10 DOI: 10.1109/ICAR.2017.8023657

G. Rigatos, P. Siano, P. Wira, K. Busawon, R. Binns

{"title":"Nonlinear optimal control for autonomous navigation of a truck and trailer system","authors":"G. Rigatos, P. Siano, P. Wira, K. Busawon, R. Binns","doi":"10.1109/ICAR.2017.8023657","DOIUrl":"https://doi.org/10.1109/ICAR.2017.8023657","url":null,"abstract":"A solution to the problem of autonomous navigation of a truck and trailer system is developed using a nonlinear optimal control method. The kinematic model of the autonomous vehicle undergoes linearization through Taylor series expansion. The linearization is performed at a temporary operating point (equilibrium) that is re-computed at each time instant using the present value of the state vector and the last value of the control inputs vector. The linearization is based on the Jacobian matrices of the model. For the linearized equivalent model of the truck and trailer system an H-infinity feedback controller is designed. The feedback control gain is obtained from the solution of an algebraic Riccati equation at each iteration of the control algorithm. The stability of the control loop is proven with Lyapunov analysis. It is demonstrated that the control loop exhibits the H-infinity tracking performance which signifies elevated robustness against modelling errors and external disturbances. Moreover, under moderate conditions the global asymptotic stability of the control loop is assured. Finally, to implement state estimation-based control for the autonomous vehicle, through the processing of a small number of sensor measurements, the H-infinity Kalman Filter is proposed.","PeriodicalId":198633,"journal":{"name":"2017 18th International Conference on Advanced Robotics (ICAR)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114410466","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: 10

Formation control of quadrotor UAVs without linear velocity measurements 无线速度测量的四旋翼无人机编队控制

2017 18th International Conference on Advanced Robotics (ICAR) Pub Date : 2017-07-10 DOI: 10.1109/ICAR.2017.8023515

Zhiqiang Miao, Yunhui Liu, Yaonan Wang, R. Fierro

引用次数: 9

Automate robot reaching task with learning from demonstration 通过示范学习自动化机器人完成任务

2017 18th International Conference on Advanced Robotics (ICAR) Pub Date : 2017-07-10 DOI: 10.1109/ICAR.2017.8023663

Jie Chen, Hongliang Ren, H. Lau

引用次数: 1