2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids)最新文献

Low-Latency Immersive 6D Televisualization with Spherical Rendering 低延迟沉浸式6D电视可视化球面渲染

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2021-07-19 DOI: 10.1109/HUMANOIDS47582.2021.9555797

M. Schwarz, Sven Behnke

引用次数: 8

Design and Development of a Flying Humanoid Robot Platform with Bi-copter Flight Unit 带双旋翼飞行单元的仿人机器人飞行平台的设计与研制

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2021-07-19 DOI: 10.1109/HUMANOIDS47582.2021.9555801

T. Anzai, Yuta Kojio, Tasuku Makabe, K. Okada, M. Inaba

引用次数: 8

Feature-based Deep Learning of Proprioceptive Models for Robotic Force Estimation 基于特征的本体感觉模型深度学习用于机器人力估计

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2021-07-19 DOI: 10.1109/HUMANOIDS47582.2021.9555682

Erik Berger, Alexander Uhlig

{"title":"Feature-based Deep Learning of Proprioceptive Models for Robotic Force Estimation","authors":"Erik Berger, Alexander Uhlig","doi":"10.1109/HUMANOIDS47582.2021.9555682","DOIUrl":"https://doi.org/10.1109/HUMANOIDS47582.2021.9555682","url":null,"abstract":"Safe and meaningful interaction with robotic systems during behavior execution requires accurate sensing capabilities. This can be achieved by the usage of force-torque sensors which are often heavy, expensive, and require an additional power supply. Consequently, providing accurate sensing capabilities to lightweight robots, with a limited amount of load, is a challenging task. Furthermore, such sensors are not able to distinguish between task-specific regular forces and external influences as induced by human co-workers. To solve this, robots often rely on a large number of manually generated rules which is a time-consuming procedure. This paper presents a data-driven machine learning approach that enhances robotic behavior with estimates of the expected proprioceptive forces (intrinsic) and unexpected forces (extrinsic) exerted by the environment. First, the robot’s common internal sensors are recorded together with ground truth measurements of the actual forces during regular and perturbed behavior executions. The resulting data is used to generate features that contain a compact representation of behavior-specific intrinsic and extrinsic fluctuations. Those features are then utilized for deep learning of proprioceptive models which enables a robot to accurately distinguish the amount of intrinsic and extrinsic forces. Experiments performed with the UR5 robot show a substantial improvement in accuracy over force values provided by previous research.","PeriodicalId":320510,"journal":{"name":"2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123826325","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

Pseudo Direct and Inverse Optimal Control based on Motion Synthesis using FPCA 基于FPCA运动合成的伪正逆最优控制

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2021-07-19 DOI: 10.1109/HUMANOIDS47582.2021.9555773

Soya Shimizu, K. Ayusawa, G. Venture

引用次数: 0

From Space to Earth – Relative-CoM-to-Foot (RCF) control yields high contact robustness 从空间到地球-相对com到脚(RCF)控制产生高接触鲁棒性

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2021-07-19 DOI: 10.1109/HUMANOIDS47582.2021.9555804

Johannes Englsberger, A. Giordano, Achraf Hiddane, R. Schuller, F. Loeffl, George Mesesan, C. Ott

引用次数: 0

Combining Task and Motion Planning using Policy Improvement with Path Integrals 结合任务和运动规划使用策略改进与路径积分

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2021-07-19 DOI: 10.1109/HUMANOIDS47582.2021.9555684

Dominik Urbaniak, Alejandro Agostini, Dongheui Lee

{"title":"Combining Task and Motion Planning using Policy Improvement with Path Integrals","authors":"Dominik Urbaniak, Alejandro Agostini, Dongheui Lee","doi":"10.1109/HUMANOIDS47582.2021.9555684","DOIUrl":"https://doi.org/10.1109/HUMANOIDS47582.2021.9555684","url":null,"abstract":"Task and motion planning deals with complex tasks that require a robot to automatically define and execute multi-step sequences of actions in cluttered scenarios. In this context, a linear motion is often not sufficient to approach a target object since collisions of the gripper with other objects or the target object might occur. Thus, motion planners should be able to generate collision-free trajectories for every particular configuration of obstacles for grounding the symbolic actions of the task plan. Current approaches either search for feasible motions offline using computationally expensive trial-and-error processes on physically realistic simulations or learn a set of motion parameters for particular object configuration spaces with little generalization. This work proposes an appealing alternative by efficiently generating trajectories for the collision-free execution of symbolic actions in variable scenarios without the need of intensive offline simulations. Our approach combines the benefit of learning from demonstration, to quickly generate an initial set of motion parameters for each symbolic action, with policy improvement with path integrals, to diversify this initial set of parameters to cope with different obstacle configurations. We show how the improved flexibility is achieved after a few minutes of training and successfully solves tasks requiring different sequences of picking and placing actions in variable configurations of obstacles.","PeriodicalId":320510,"journal":{"name":"2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132450363","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

Development of Amphibious Humanoid for Behavior Acquisition on Land and Underwater 陆地和水下行为采集两栖类机器人的研制

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2021-07-19 DOI: 10.1109/HUMANOIDS47582.2021.9555671

Tasuku Makabe, T. Anzai, Youhei Kakiuchi, K. Okada, M. Inaba

{"title":"Development of Amphibious Humanoid for Behavior Acquisition on Land and Underwater","authors":"Tasuku Makabe, T. Anzai, Youhei Kakiuchi, K. Okada, M. Inaba","doi":"10.1109/HUMANOIDS47582.2021.9555671","DOIUrl":"https://doi.org/10.1109/HUMANOIDS47582.2021.9555671","url":null,"abstract":"Humanoid research aimed at verifying human movements and substituting for work deals with movement acquisition in various environments to which humans can adapt. On the other hand, water exists as an environment in which humanoids cannot adapt, even though humans adapt and demand work alternatives. Therefore, there is room to construct a platform that can operate underwater and the ground and verify the method of acquiring operation underwater. This study constructs the humanoid that can operate in both land and water environments using modular components that can easily change the body structure. While changing the environment’s force, such as frictional force, water resistance, and buoyancy, the humanoid performed moving movements such as swimming and walking in multiple lands and water settings. Walking motion experiments have shown that the underwater environment’s viscosity effectively reduces the speed of falls and prevents damage in humanoid experiments. We investigated a solution to the problem that humanoids are vulnerable to disturbance in an environment where friction is brutal to obtain through swimming.","PeriodicalId":320510,"journal":{"name":"2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134641307","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

Motion Modification Method of Musculoskeletal Humanoids by Human Teaching Using Muscle-Based Compensation Control 基于肌肉补偿控制的人体教学中肌肉骨骼类人形机器人运动修饰方法

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2021-07-19 DOI: 10.1109/HUMANOIDS47582.2021.9555772

Kento Kawaharazuka, Yuya Koga, Manabu Nishiura, Yusuke Omura, Yuki Asano, K. Okada, Koji Kawasaki, M. Inaba

引用次数: 0

An Integrated, Force-Sensitive, Impedance Controlled, Tendon-Driven Wrist: Design, Modeling, and Control 一个集成的，力敏感的，阻抗控制的，肌腱驱动的手腕:设计，建模和控制

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2021-07-19 DOI: 10.1109/HUMANOIDS47582.2021.9555777

Alexander Toedtheide, Johannes Kühn, Edmundo Pozo Fortunic, S. Haddadin

{"title":"An Integrated, Force-Sensitive, Impedance Controlled, Tendon-Driven Wrist: Design, Modeling, and Control","authors":"Alexander Toedtheide, Johannes Kühn, Edmundo Pozo Fortunic, S. Haddadin","doi":"10.1109/HUMANOIDS47582.2021.9555777","DOIUrl":"https://doi.org/10.1109/HUMANOIDS47582.2021.9555777","url":null,"abstract":"This paper presents a novel 2 degrees of freedom humanoid wrist with solely three tendons, based on an integrated 3S$overline{P}$S-1U parallel kinematics (the $overline{P}$ indicates the active degree of freedom) and driven by three electromechanical motors. Tendon-force measurement and control, combined with nonlinear kinematics mapping enable the implementation of a oint-level impedance controller, virtual walls, a momentum oberver and a virtual joint-torque sensor. The novel mechanical esign, especially the drive-train and the tendon force measurenent module, are discussed in the paper. Simulations show the easibility of the control methods. A static workspace analysis - eveals a configuration depending torque with a theoretical maximum torque of 6.1 Nm or 9.3 Nm (depending on the used gear ratio). All control modes as well as human interaction are validated experimentally. First experiments on a humanoid arm are shown. An experimental performance of a maximum speed of 400 deg/s, a maximum payload of 2.5 kg (lever arm 16 cm) and an accuracy of less than 0.1 deg (95% confidence interval) are achieved.","PeriodicalId":320510,"journal":{"name":"2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114579934","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

A vertical jump optimization strategy for one-legged robot with variable reduction ratio joint 可变减速比单足机器人垂直跳跃优化策略

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2021-07-19 DOI: 10.1109/HUMANOIDS47582.2021.9555679

Haoxiang Qi, Xuechao Chen, Zhangguo Yu, Gao Huang, Libo Meng, K. Hashimoto, Wen-Xiong Liao, Qiang Huang

引用次数: 2