2015 International Conference on Advanced Robotics (ICAR)最新文献_第3页

Real-time motion adaptation using relative distance space representation 使用相对距离空间表示的实时运动适应

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251428

Yiming Yang, V. Ivan, S. Vijayakumar

引用次数: 18

Optimization of the switching surface for the simplest passive dynamic biped 最简单被动动态两足机器人切换面优化

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251481

A. Safa, M. Naraghi, A. Alasty

引用次数: 2

Acquisition of grounded models of adjectival modifiers supporting semantic composition and transfer to a physical interactive robot 支持语义组合的形容词修饰语基础模型的获取和向物理交互机器人的迁移

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251463

N. Mavridis, S. Kundig, N. Kapellas

{"title":"Acquisition of grounded models of adjectival modifiers supporting semantic composition and transfer to a physical interactive robot","authors":"N. Mavridis, S. Kundig, N. Kapellas","doi":"10.1109/ICAR.2015.7251463","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251463","url":null,"abstract":"Compositionality is a property of natural language which is of prime importance: It enables humans to form and conceptualize potentially novel and complex ideas, by combining words. On the other hand, the symbol grounding problem examines the way meaning is anchored to entities external to language, such as sensory percepts and sensory-motor routines. In this paper we aim towards the exploration of the intersection of compositionality and symbol grounding. We thus propose a methodology for constructing empirically derived models of grounded meaning, which afford composition of grounded semantics. We illustrate our methodology for the case of adjectival modifiers. Grounded models of adjectively modified and unmodified colors are acquired through a specially designed procedure with 134 participants, and then computational models of the modifiers “dark” and “light” are derived. The generalization ability of these learnt models is quantitatively evaluated, and their usage is demonstrated in a real-world physical humanoid robot. We regard this as an important step towards extending empirical approaches for symbol grounding so that they can accommodate compositionality: a necessary step towards the deep understanding of natural language for situated embodied agents, such as sensor-enabled ambient intelligence and interactive robots.","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":"114576367","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

Interaction modeling in the grasping and manipulation of 3D deformable objects 三维可变形物体抓取与操纵中的交互建模

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251503

L. Zaidi, B. Bouzgarrou, L. Sabourin, Y. Mezouar

引用次数: 10

Model predictive path planning with time-varying safety constraints for highway autonomous driving 基于时变安全约束的高速公路自动驾驶预测路径规划模型

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251458

Mehdi Jalalmaab, B. Fidan, Soo Jeon, P. Falcone

引用次数: 30

Real-time needle tip localization in 2D ultrasound images for robotic biopsies 用于机器人活检的二维超声图像的实时针尖定位

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251432

Mert Kaya, Enes Senel, Awais Ahmad, Orcun Orhan, O. Bebek

引用次数: 22

Pushing and grasping for autonomous learning of object models with foveated vision 聚焦视觉下物体模型自主学习的推动与抓取

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251462

Robert Bevec, A. Ude

{"title":"Pushing and grasping for autonomous learning of object models with foveated vision","authors":"Robert Bevec, A. Ude","doi":"10.1109/ICAR.2015.7251462","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251462","url":null,"abstract":"In this paper we address the problem of autonomous learning of visual appearance of unknown objects. We propose a method that integrates foveated vision on a humanoid robot with autonomous object discovery and explorative manipulation actions such as pushing, grasping, and in-hand rotation. The humanoid robot starts by searching for objects in a visual scene and generating hypotheses about which parts of the visual scene could constitute an object. The hypothetical objects are verified by applying pushing actions, where the existence of an object is considered confirmed if the visual features exhibit rigid body motion. In our previous work we showed that partial object models can be learnt by a sequential application of several robot pushes, which generates the views of object appearance from different viewpoints. However, with this approach it is not possible to guarantee that the object will be seen from all relevant viewpoints even after a large number of pushes have been carried out. Instead, in this paper we show that confirmed object hypotheses contain enough information to enable grasping and that object models can be acquired more effectively by sequentially rotating the object. We show the effectiveness of our new system by comparing object recognition results after the robot learns object models by two different approaches: 1. learning from images acquired by several pushes and 2. learning from images acquired by an initial push followed by several grasp-rotate-release action cycles.","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":"129219635","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: 3

Toward data-driven models of legged locomotion using harmonic transfer functions 基于谐波传递函数的腿部运动数据驱动模型研究

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251480

Ismail Uyanik, M. M. Ankaralı, N. Cowan, Ö. Morgül, U. Saranlı

{"title":"Toward data-driven models of legged locomotion using harmonic transfer functions","authors":"Ismail Uyanik, M. M. Ankaralı, N. Cowan, Ö. Morgül, U. Saranlı","doi":"10.1109/ICAR.2015.7251480","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251480","url":null,"abstract":"There are limitations on the extent to which manually constructed mathematical models can capture relevant aspects of legged locomotion. Even simple models for basic behaviours such as running involve non-integrable dynamics, requiring the use of possibly inaccurate approximations in the design of model-based controllers. In this study, we show how data-driven frequency domain system identification methods can be used to obtain input-output characteristics for a class of dynamical systems around their limit cycles, with hybrid structural properties similar to those observed in legged locomotion systems. Under certain assumptions, we can approximate hybrid dynamics of such systems around their limit cycle as a piecewise smooth linear time periodic system (LTP), further approximated as a time-periodic, piecewise LTI system to reduce parametric degrees of freedom in the identification process. In this paper, we use a simple one-dimensional hybrid model in which a limit-cycle is induced through the actions of a linear actuator to illustrate the details of our method. We first derive theoretical harmonic transfer functions (HTFs) of our example model. We then excite the model with small chirp signals to introduce perturbations around its limit-cycle and present systematic identification results to estimate the HTFs for this model. Comparison between the data-driven HTFs model and its theoretical prediction illustrates the potential effectiveness of such empirical identification methods in legged locomotion.","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":"129233183","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

Pheromone averaging exploration algorithm 信息素平均探索算法

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251520

Bogdan-Florin Florea, O. Grigore, M. Datcu

引用次数: 4

Simultaneous human-robot adaptation for effective skill transfer 同时人-机器人适应有效的技能转移

2015 International Conference on Advanced Robotics (ICAR) Pub Date : 2015-07-27 DOI: 10.1109/ICAR.2015.7251437

M. Zamani, Erhan Öztop

{"title":"Simultaneous human-robot adaptation for effective skill transfer","authors":"M. Zamani, Erhan Öztop","doi":"10.1109/ICAR.2015.7251437","DOIUrl":"https://doi.org/10.1109/ICAR.2015.7251437","url":null,"abstract":"In this paper, we propose and implement a human-in-the loop robot skill synthesis framework that involves simultaneous adaptation of the human and the robot. In this framework, the human demonstrator learns to control the robot in real-time to make it perform a given task. At the same time, the robot learns from the human guided control creating a non-trivial coupled dynamical system. The research question we address is how this system can be tuned to facilitate faster skill transfer or improve the performance level of the transferred skill. In the current paper we report our initial work for the latter. At the beginning of the skill transfer session, the human demonstrator controls the robot exclusively as in teleoperation. As the task performance improves the robot takes increasingly more share in control, eventually reaching full autonomy. The proposed framework is implemented and shown to work on a physical cart-pole setup. To assess whether simultaneous learning has advantage over the standard sequential learning (where the robot learns from the human observation but does not interfere with the control) experiments with two groups of subjects were performed. The results indicate that the final autonomous controller obtained via simultaneous learning has a higher performance measured as the average deviation from the upright posture of the pole.","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":"131043054","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