2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)最新文献_第7页

Learning Robust Task Priorities of QP-Based Whole-Body Torque-Controllers 基于qp的全身转矩控制器鲁棒任务优先级学习

2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids) Pub Date : 2018-11-01 DOI: 10.1109/HUMANOIDS.2018.8624995

Marie Charbonneau, Valerio Modugno, F. Nori, G. Oriolo, D. Pucci, S. Ivaldi

{"title":"Learning Robust Task Priorities of QP-Based Whole-Body Torque-Controllers","authors":"Marie Charbonneau, Valerio Modugno, F. Nori, G. Oriolo, D. Pucci, S. Ivaldi","doi":"10.1109/HUMANOIDS.2018.8624995","DOIUrl":"https://doi.org/10.1109/HUMANOIDS.2018.8624995","url":null,"abstract":"Generating complex whole-body movements for humanoid robots is now most often achieved with multi-task whole-body controllers based on quadratic programming. To perform on the real robot, such controllers often require a human expert to tune or optimize the many parameters of the controller related to the tasks and to the specific robot, which is generally reported as a tedious and time consuming procedure. This problem can be tackled by automatically optimizing some parameters such as task priorities or task trajectories, while ensuring constraints satisfaction, through simulation. However, this does not guarantee that parameters optimized in simulation will also be optimal for the real robot. As a solution, the present paper focuses on optimizing task priorities in a robust way, by looking for solutions which achieve desired tasks under a variety of conditions and perturbations. This approach, which can be referred to as domain randomization, can greatly facilitate the transfer of optimized solutions from simulation to a real robot. The proposed method is demonstrated using a simulation of the humanoid robot iCub for a whole-body stepping task.","PeriodicalId":433345,"journal":{"name":"2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123347756","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

Target Walking Speed Generation and Parameters Identification by Feedback Control of 1-DOF Limit Cycle Walker 基于反馈控制的1自由度极限环行走器目标行走速度生成及参数辨识

2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids) Pub Date : 2018-11-01 DOI: 10.1109/HUMANOIDS.2018.8624950

Qingqing Wei, Xuan Xiao, Qingliang Meng, F. Asano

引用次数: 0

Mathematical Modeling of Human Body and Movements: On Muscle Fatigue and Recovery Based on Energy Supply Systems 人体和运动的数学建模:基于能量供应系统的肌肉疲劳和恢复

2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids) Pub Date : 2018-11-01 DOI: 10.1109/HUMANOIDS.2018.8625050

Yan Huang, Yoshihiko Nakamura, Y. Ikegami, Qiang Huang

引用次数: 0

Force Control Law Selection for Elastic Part Assembly from Human Data and Parameter Optimization 基于人体数据的弹性零件装配力控制规律选择及参数优化

2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids) Pub Date : 2018-11-01 DOI: 10.1109/HUMANOIDS.2018.8624968

Yasuhiko Fukumoto, K. Harada

引用次数: 3

Dynamic Model of Exoskeleton Based on Pneumatic Muscle Actuators and Experiment Verification 基于气动肌肉作动器的外骨骼动力学模型及实验验证

2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids) Pub Date : 2018-11-01 DOI: 10.1109/HUMANOIDS.2018.8624914

Yu Cao, Jian Huang, Zhangbo Huang, Xikai Tu, Hongge Ru, Cheng Chen, Jun Huo

引用次数: 3

Target Recognition and Heavy Load Operation Posture Control of Humanoid Robot for Trolley Operation 小车作业仿人机器人目标识别与重载作业姿态控制

2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids) Pub Date : 2018-11-01 DOI: 10.1109/HUMANOIDS.2018.8625056

Huiling Liu, Chengfang Luo, Lei Zhang

引用次数: 9

Compliant Robot Motion Regulated via Proprioceptive Sensor Based Contact Observer 基于本体感觉传感器的接触观测器调节柔性机器人运动

2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids) Pub Date : 2018-11-01 DOI: 10.1109/HUMANOIDS.2018.8624946

Anastasia Bolotnikova, S. Courtois, A. Kheddar

引用次数: 4

Online Learning of an Open-Ended Skill Library for Collaborative Tasks 开放式协作任务技能库的在线学习

2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids) Pub Date : 2018-11-01 DOI: 10.1109/HUMANOIDS.2018.8625031

Dorothea Koert, Susanne Trick, Marco Ewerton, M. Lutter, Jan Peters

{"title":"Online Learning of an Open-Ended Skill Library for Collaborative Tasks","authors":"Dorothea Koert, Susanne Trick, Marco Ewerton, M. Lutter, Jan Peters","doi":"10.1109/HUMANOIDS.2018.8625031","DOIUrl":"https://doi.org/10.1109/HUMANOIDS.2018.8625031","url":null,"abstract":"Intelligent robotic assistants can potentially improve the quality of life for elderly people and help them maintain their independence. However, the number of different and personalized tasks render pre-programming of such assistive robots prohibitively difficult. Instead, to cope with a continuous and open-ended stream of cooperative tasks, new collaborative skills need to be continuously learned and updated from demonstrations. To this end, we introduce an online learning method for a skill library of collaborative tasks that employs an incremental mixture model of probabilistic interaction primitives. This model chooses a corresponding robot response to a human movement where the human intention is extracted from previously demonstrated movements. Unlike existing batch methods of movement primitives for human-robot interaction, our approach builds a library of skills online, in an open-ended fashion and updates existing skills using new demonstrations. The resulting approach was evaluated both on a simple benchmark task and in an assistive human-robot collaboration scenario with a 7DoF robot arm.","PeriodicalId":433345,"journal":{"name":"2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133755118","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

Towards Improving Myocontrol of Prosthetic Hands: A Study on Automated Instability Detection 改进假手肌肉控制:不稳定自动检测的研究

2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids) Pub Date : 2018-11-01 DOI: 10.1109/HUMANOIDS.2018.8625021

R. Meattini, Markus Nowak, C. Melchiorri, Claudio Castellini

{"title":"Towards Improving Myocontrol of Prosthetic Hands: A Study on Automated Instability Detection","authors":"R. Meattini, Markus Nowak, C. Melchiorri, Claudio Castellini","doi":"10.1109/HUMANOIDS.2018.8625021","DOIUrl":"https://doi.org/10.1109/HUMANOIDS.2018.8625021","url":null,"abstract":"Myocontrol is the control of an assistive device via the interpretation of the subject's intent using surface electromyography, and one paradigmatic instance of myocontrol is in upper-limb prosthetics applications. The reliability of this kind of control remains a key issue - effective and stable upper-limb myocontrol is one of the most interesting open problems in the field of human-robot interfaces and rehabilitation. In this work we focused on the myocontrol of a prosthetic hand while grasping: performing grasp actions only when, and exactly for the duration, the user desires, avoiding failures that can lead to frustrating or catastrophic results. One specific step to improve stability in the myocontrol of prosthetic hands is the possibility to automatically detect the occurrence of a failure. For this purpose, the availability of an automatic “oracle” able to accomplish this work enables the possibility of self-adaptation of the myocontrol system - e.g. via on-demand model updates for incremental learning. According to this view, we performed an experiment using a simplified but still realistic grasping protocol involving four able-bodied expert myocontrol users, and we extracted features from a state-of-the-art commercial prosthetic hand to automatically identify instability in the myocontrol. The results show that a standard classifier is able to detect failures with a mean balanced error rate of 15.98% over the subjects that took part in the experiments. Our results can also be potentially applied in non-medical applications such as, e.g., teleoperation using extra-light interfaces.","PeriodicalId":433345,"journal":{"name":"2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131318120","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

Temporal Concurrent Planning with Stressed Actions 有压力行动的时间并发计划

2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids) Pub Date : 2018-11-01 DOI: 10.1109/HUMANOIDS.2018.8625020

Fabian Peller, Mirko Wächter, Markus Grotz, P. Kaiser, T. Asfour

{"title":"Temporal Concurrent Planning with Stressed Actions","authors":"Fabian Peller, Mirko Wächter, Markus Grotz, P. Kaiser, T. Asfour","doi":"10.1109/HUMANOIDS.2018.8625020","DOIUrl":"https://doi.org/10.1109/HUMANOIDS.2018.8625020","url":null,"abstract":"Temporal stress is something that humans have to face nearly every day. Humans have to handle situations, where there is not much time left for a specific task. Most robotic systems, on the other hand, are not able to act in such temporally unstructured environments. For that reason, we present the novel Temporal Stressing Fast Downward (TSFD)planning system based on Temporal Fast Downward (TFD), which solves temporal problems using a modified heuristic forward search. With this planner, we introduce the novel concept of stressed actions for temporally bounded problems. Stressed actions enable a robot to accelerate or decelerate actions under consideration of an action-specific temporal cost function and the available time for plan execution. We further introduce an improved decision epoch search that allows complete planning with temporal gaps. Our evaluation in benchmark domains and on the real humanoid robot ARMAR-III shows that TSFD has the ability to produce plans of better makespan than TFD and is able to solve problems that could not be handled before. Furthermore, TSFD performs better in typical service robotics tasks than baseline approaches. Finally, we show that stressed actions greatly increase the possibility of finding feasible solutions in temporally bounded tasks.","PeriodicalId":433345,"journal":{"name":"2018 IEEE-RAS 18th International Conference on Humanoid Robots (Humanoids)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114523241","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