2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)最新文献_第9页

Learning deep movement primitives using convolutional neural networks 使用卷积神经网络学习深度运动原语

2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids) Pub Date : 2017-11-01 DOI: 10.1109/HUMANOIDS.2017.8246874

Affan Pervez, Yuecheng Mao, Dongheui Lee

引用次数: 49

Efficient coverage of 3D environments with humanoid robots using inverse reachability maps 利用逆可达性图实现仿人机器人对三维环境的有效覆盖

2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids) Pub Date : 2017-11-01 DOI: 10.1109/HUMANOIDS.2017.8239550

Stefan Oßwald, P. Karkowski, Maren Bennewitz

引用次数: 16

Collision-free trajectory planning in human-robot interaction through hand movement prediction from vision 基于视觉手部运动预测的人机交互无碰撞轨迹规划

2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids) Pub Date : 2017-11-01 DOI: 10.1109/HUMANOIDS.2017.8246890

Yiwei Wang, Xin Ye, Yezhou Yang, Wenlong Zhang

{"title":"Collision-free trajectory planning in human-robot interaction through hand movement prediction from vision","authors":"Yiwei Wang, Xin Ye, Yezhou Yang, Wenlong Zhang","doi":"10.1109/HUMANOIDS.2017.8246890","DOIUrl":"https://doi.org/10.1109/HUMANOIDS.2017.8246890","url":null,"abstract":"We present a framework from vision based hand movement prediction in a real-world human-robot collaborative scenario for safety guarantee. We first propose a perception submodule that takes in visual data solely and predicts human collaborator's hand movement. Then a robot trajectory adaptive planning submodule is developed that takes the noisy movement prediction signal into consideration for optimization. To validate the proposed systems, we first collect a new human manipulation dataset that can supplement the previous publicly available dataset with motion capture data to serve as the ground truth of hand location. We then integrate the algorithm with a six degree-of-freedom robot manipulator that can collaborate with human workers on a set of trained manipulation actions, and it is shown that such a robot system outperforms the one without movement prediction in terms of collision avoidance. We verify the effectiveness of the proposed motion prediction and robot trajectory planning approaches in both simulated and physical experiments. To the best of the authors' knowledge, it is the first time that a deep model based movement prediction system is utilized and is proven effective in human-robot collaboration scenario for enhanced safety.","PeriodicalId":143992,"journal":{"name":"2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121171970","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: 21

Tactile-based object center of mass exploration and discrimination 基于触觉的物体中心的大规模探索和辨别

2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids) Pub Date : 2017-11-01 DOI: 10.1109/HUMANOIDS.2017.8246975

Kunpeng Yao, Mohsen Kaboli, G. Cheng

{"title":"Tactile-based object center of mass exploration and discrimination","authors":"Kunpeng Yao, Mohsen Kaboli, G. Cheng","doi":"10.1109/HUMANOIDS.2017.8246975","DOIUrl":"https://doi.org/10.1109/HUMANOIDS.2017.8246975","url":null,"abstract":"In robotic tasks, object recognition and discrimination can be realized according to their physical properties, such as color, shape, stiffness, and surface textures. However, these external properties may fail if they are similar or even identical. In this case, internal properties of the objects can be considered, for example, the center of mass. Center of mass is an important inherent physical property of objects; however, due to the difficulties in its determination, it has never been applied in object discrimination tasks. In this work, we present a tactile-based approach to explore the center of mass of rigid objects and apply it in robotic object discrimination tasks. This work comprises three aspects: (a) continuous estimation of the target object's geometric information, (b) exploration of the center of mass, and (c) object discrimination based on the center of mass features. Experimental results show that by following our proposed approach, the center of mass of experimental objects can be accurately estimated, and objects of identical external properties but different mass distributions can be successfully discriminated. Our approach is also robust against the textural properties and stiffness of experimental objects.","PeriodicalId":143992,"journal":{"name":"2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125804649","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: 24

Reflex control of body posture in standing 站立时身体姿势的反射控制

2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids) Pub Date : 2017-11-01 DOI: 10.1109/HUMANOIDS.2017.8246883

A. Sarmadi, Maziar Ahmad Sharbafi, A. Seyfarth

引用次数: 4

Task level hierarchical system for BCI-enabled shared autonomy 支持bci的共享自治的任务级分层系统

2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids) Pub Date : 2017-11-01 DOI: 10.1109/HUMANOIDS.2017.8246878

Iretiayo Akinola, Boyuan Chen, Jonathan Koss, Aalhad Patankar, Jacob Varley, P. Allen

引用次数: 14

The complexities of grasping in the wild 野外抓握的复杂性

2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids) Pub Date : 2017-11-01 DOI: 10.1109/HUMANOIDS.2017.8246880

Yuzuko C. Nakamura, Daniel M. Troniak, Alberto Rodriguez, M. T. Mason, N. Pollard

引用次数: 22

Remote control for redundant humanoid arm using optimized arm angle 基于优化臂角的冗余仿人臂远程控制

2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids) Pub Date : 2017-11-01 DOI: 10.1109/HUMANOIDS.2017.8246893

Jaesung Oh, Buyoun Cho, Jun-Ho Oh

引用次数: 4

Robust foot placement control for dynamic walking using online parameter estimation 基于在线参数估计的动态步行鲁棒足位控制

2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids) Pub Date : 2017-11-01 DOI: 10.1109/HUMANOIDS.2017.8239552

Qingbiao Li, Iordanis Chatzinikolaidis, Yiming Yang, S. Vijayakumar, Zhibin Li

引用次数: 7

Improving the scalability of asymptotically optimal motion planning for humanoid dual-arm manipulators 提高类人双臂机械臂渐近最优运动规划的可扩展性

2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids) Pub Date : 2017-11-01 DOI: 10.1109/HUMANOIDS.2017.8246885

Rahul Shome, Kostas E. Bekris

{"title":"Improving the scalability of asymptotically optimal motion planning for humanoid dual-arm manipulators","authors":"Rahul Shome, Kostas E. Bekris","doi":"10.1109/HUMANOIDS.2017.8246885","DOIUrl":"https://doi.org/10.1109/HUMANOIDS.2017.8246885","url":null,"abstract":"Due to high-dimensionality, many motion planners for dual-arm systems follow a decoupled approach, which does not provide guarantees. Asymptotically optimal sampling-based planners provide guarantees but in practice face scalability challenges. This work improves the computational scalability of the latter methods in this domain. It builds on top of recent advances in multi-robot motion planning, which provide guarantees without having to explicitly construct a roadmap in the composite space of all robots. The proposed framework builds roadmaps for components of a humanoid robot's kinematic chain. Then, the tensor product of these component roadmaps is searched implicitly online in a way that asymptotic optimality is provided. Appropriate heuristics from the component roadmaps are utilized for discovering the solution in the composite space effectively. Evaluation on various dual-arm problems show that the method returns paths of increasing quality, has significantly reduced space requirements and improved convergence rate relative to the standard asymptotically optimal approaches.","PeriodicalId":143992,"journal":{"name":"2017 IEEE-RAS 17th International Conference on Humanoid Robotics (Humanoids)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115973975","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: 6