2015 International Conference on Advanced Robotics (ICAR)最新文献

On the EMG-based torque estimation for humans coupled with a force-controlled elbow exoskeleton 结合力控肘外骨骼的肌电转矩估计研究

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-09-10 DOI: 10.1109/ICAR.2015.7251472

J. B. Ullauri, L. Peternel, B. Ugurlu, Yoji Yamada, J. Morimoto

引用次数: 7

Transferring object grasping knowledge and skill across different robotic platforms 在不同机器人平台之间传递物体抓取知识和技能

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251502

A. Paikan, David Schiebener, Mirko Wächter, T. Asfour, G. Metta, L. Natale

引用次数: 8

Cooperative control of manipulator robotic systems with unknown dynamics 未知动力学下机械臂机器人系统的协同控制

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251487

E. Mehrabi, H. Talebi, M. Zarei-nejad, I. Sharifi

引用次数: 3

Dynamic process migration in heterogeneous ROS-based environments 基于ros的异构环境中的动态流程迁移

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251505

José Cano, Eduardo J. Molinos, V. Nagarajan, S. Vijayakumar

{"title":"Dynamic process migration in heterogeneous ROS-based environments","authors":"José Cano, Eduardo J. Molinos, V. Nagarajan, S. Vijayakumar","doi":"10.1109/ICAR.2015.7251505","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251505","url":null,"abstract":"In distributed (mobile) robotics environments, the different computing substrates offer flexible resource allocation options to perform computations that implement an overall system goal. The AnyScale concept that we introduce and describe in this paper exploits this redundancy by dynamically allocating tasks to appropriate substrates (or scales) to optimize some level of system performance while migrating others depending on current resource and performance parameters. In this paper, we demonstrate this concept with a general ROS-based infrastructure that solves the task allocation problem by optimising the system performance while correctly reacting to unpredictable events at the same time. Assignment decisions are based on a characterisation of the static/dynamic parameters that represent the system and its interaction with the environment. We instantiate our infrastructure on a case study application, in which a mobile robot navigates along the floor of a building trying to reach a predefined goal. Experimental validation demonstrates more robust performance (around a third improvement in metrics) under the Anyscale implementation framework.","PeriodicalId":432004,"journal":{"name":"2015 International Conference on Advanced Robotics (ICAR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126182202","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

Robot-mediated mixed gesture imitation skill training for young children with ASD 机器人介导的幼儿ASD混合手势模仿技能训练

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251436

Zhi Zheng, Eric M. Young, A. Swanson, A. Weitlauf, Z. Warren, N. Sarkar

引用次数: 7

GMM-based detection of human hand actions for robot spatial attention 基于gmm的人手动作检测对机器人空间注意力的影响

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251500

Riccardo Monica, J. Aleotti, S. Caselli

引用次数: 0

Reactive, task-specific object manipulation by metric reinforcement learning 通过度量强化学习的反应性、任务特定对象操作

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251511

Simon Hangl, Emre Ugur, S. Szedmák, J. Piater, A. Ude

{"title":"Reactive, task-specific object manipulation by metric reinforcement learning","authors":"Simon Hangl, Emre Ugur, S. Szedmák, J. Piater, A. Ude","doi":"10.1109/ICAR.2015.7251511","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251511","url":null,"abstract":"In the context of manipulation of dynamical systems, it is not trivial to design controllers that can cope with unpredictable changes in the system being manipulated. For example, in a pouring task, the target cup might start moving or the agent may decide to change the amount of the liquid during action execution. In order to cope with these situations, the robot should smoothly (and timely) change its execution policy based on the requirements of the new situation. In this paper, we propose a robust method that allows the robot to smoothly and successfully react to such changes. The robot first learns a set of execution trajectories that can solve a number of tasks in different situations. When encountered with a novel situation, the robot smoothly adapts its trajectory to a new one that is generated by weighted linear combination of the previously learned trajectories, where the weights are computed using a metric that depends on the task. This task-dependent metric is automatically learned in the state space of the robot, rather than the motor control space, and further optimized using using reinforcement learning (RL) framework. We discuss that our system can learn and model various manipulation tasks such as pouring or reaching; and can successfully react to a wide range of perturbations introduced during task executions. We evaluated our method against ground truth with a synthetic trajectory dataset, and verified it in grasping and pouring tasks with a real robot.","PeriodicalId":432004,"journal":{"name":"2015 International Conference on Advanced Robotics (ICAR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128564001","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: 12

Visual matching of stroke order in robotic calligraphy 机器人书法中笔画顺序的视觉匹配

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251496

Hsien-I Lin, Yu-Che Huang

{"title":"Visual matching of stroke order in robotic calligraphy","authors":"Hsien-I Lin, Yu-Che Huang","doi":"10.1109/ICAR.2015.7251496","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251496","url":null,"abstract":"Robotic calligraphy is an interesting problem and recently draws much attention. Two major problems in robotic calligraphy are stroke shape and stroke order. Most of previous work focused on controlling brush trajectory, pressure, velocity, and acceleration to draw a desired stroke shape. As for stroke order, it was manually given from a database. Even for a software of optical character recognition (OCR), it cannot recognize the stroke order from a character image. This paper describes the automatic extraction of the stroke order of a Chinese character by visual matching. Specifically speaking, the stroke order of a Chinese character on an image can be automatically generated by the association of the standard image of the same character given with its stroke order. The proposed visual-matching method extracts the features of the Hough Lines of an input image and uses support vector machine (SVM) to associate the features with the ones of the standard image. The features used in the proposed method were evaluated on several Chinese characters. Two famous Chinese characters “Country” and “Dragon” were used to demonstrate the feasibility of the proposed method. The matched rate of the stroke order of “Country” and “Dragon” were 95.8% and 90.3%, respectively.","PeriodicalId":432004,"journal":{"name":"2015 International Conference on Advanced Robotics (ICAR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114064728","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: 9

A high frequency 3D LiDAR with enhanced measurement density via Papoulis-Gerchberg 通过Papoulis-Gerchberg增强测量密度的高频3D激光雷达

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251509

Bengisu Ozbay, Elvan Kuzucu, M. Gul, Dilan Ozturk, M. Tasci, A. Arisoy, H. Sirin, Ismail Uyanik

{"title":"A high frequency 3D LiDAR with enhanced measurement density via Papoulis-Gerchberg","authors":"Bengisu Ozbay, Elvan Kuzucu, M. Gul, Dilan Ozturk, M. Tasci, A. Arisoy, H. Sirin, Ismail Uyanik","doi":"10.1109/ICAR.2015.7251509","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251509","url":null,"abstract":"Light Detection and Ranging (LiDAR) devices are gaining more importance for obtaining sensory information in mobile robot applications. However, existing solutions in literature yield low frequency outputs with huge measurement delay to obtain 3D range image of the environment. This paper introduces the design and construction of a 3D range sensor based on rotating a 2D LiDAR around its pitch axis. Different than previous approaches, we adjust our scan frequency to 5 Hz to support its application on mobile robot platforms. However, increasing scan frequency drastically reduces the measurement density in 3D range images. Therefore, we propose two post-processing algorithms to increase measurement density while keeping the 3D scan frequency at an acceptable level. To this end, we use an extended version of the Papoulis-Gerchberg algorithm to achieve super-resolution on 3D range data by estimating the unmeasured samples in the environment. In addition, we propose a probabilistic obstacle reconstruction algorithm to consider the probabilities of the estimated (virtual) points and to obtain a very fast prediction about the existence and shape of the obstacles.","PeriodicalId":432004,"journal":{"name":"2015 International Conference on Advanced Robotics (ICAR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115976916","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

Subjective difficulty and indicators of performance of joystick-based robot arm teleoperation with auditory feedback 基于听觉反馈的操纵杆机械臂遥操作的主观难度和性能指标

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251439

N. Mavridis, G. Pierris, P. Gallina, N. Moustakas, A. Astaras

{"title":"Subjective difficulty and indicators of performance of joystick-based robot arm teleoperation with auditory feedback","authors":"N. Mavridis, G. Pierris, P. Gallina, N. Moustakas, A. Astaras","doi":"10.1109/ICAR.2015.7251439","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251439","url":null,"abstract":"Joystick-based teleoperation is a dominant method for remotely controlling various types of robots, such as excavators, cranes, and space telerobotics. Our ultimate goal is to create effective methods for training and assessing human operators of joystick-controlled robots. Towards that goal, an extensive study consisting of a total of 38 experimental subjects on both simulated as well as a physical robot, using either no feedback or auditory feedback, has been performed. In this paper, we present the complete experimental setup and we report only on the 18 experimental subjects teleoperating the simulated robot. Multiple observables were recorded, including not only joystick and robot angles and timings, but also subjective measures of difficulty, personality and usability data, and automated analysis of facial expressions and blink rate of the subjects. Our initial results indicate that: First, that the subjective difficulty of teleoperation with auditory feedback has smaller variance as compared to teleoperation without feedback. Second, that the subjective difficulty of a task is linearly related with the logarithm of task completion time. Third, we introduce two important indicators of operator performance, namely the Average Velocity of Robot Joints (AVRJ), and the Correct-to-Wrong-Joystick Direction Ratio (CWJR), and we show how these relate to accumulated user experience and with task time. We conclude with a forward-looking discussion including future steps.","PeriodicalId":432004,"journal":{"name":"2015 International Conference on Advanced Robotics (ICAR)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134061312","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