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

Robust Balancing Control of a Spring-legged Robot based on a High-order Sliding Mode Observer 基于高阶滑模观测器的弹簧腿机器人鲁棒平衡控制

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2021-07-19 DOI: 10.1109/HUMANOIDS47582.2021.9555776

Juan D. Gamba, A. C. Leite, R. Featherstone

{"title":"Robust Balancing Control of a Spring-legged Robot based on a High-order Sliding Mode Observer","authors":"Juan D. Gamba, A. C. Leite, R. Featherstone","doi":"10.1109/HUMANOIDS47582.2021.9555776","DOIUrl":"https://doi.org/10.1109/HUMANOIDS47582.2021.9555776","url":null,"abstract":"This paper presents a simulation study of the balancing problem for a monopod robot in which the lower body (the leg) has been modified to include a passively spring-loaded prismatic joint. Such a mechanism can move by hopping but can also stand and balance on a single point. We aim to investigate the extent to which a balance controller can deal with the large values and rapid changes in the spring-damper forces, while controlling the absolute positions and orientations of its parts and balancing on one leg. It can be shown that a good performance is achieved if the spring-loaded joint is instrumented and calibrated so that its position and velocity, as well as the stiffness and damping coefficients, are considered when calculating the controller state variables. We also demonstrate the effectiveness of the balance controller by adding a high-order sliding mode (HOSM) observer based on the finite-time algorithm for robust parameter estimation of the stiffness and damping coefficients. The stability analysis and convergence proofs are presented based on the Lyapunov stability theory. Numerical simulations are included to illustrate the performance and feasibility of the proposed methodology.","PeriodicalId":320510,"journal":{"name":"2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids)","volume":"110 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":"115450553","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

Identification of Common Force-based Robot Skills from the Human and Robot Perspective 基于人与机器人视角的常见力机器人技能识别

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2021-07-19 DOI: 10.1109/HUMANOIDS47582.2021.9555681

Thomas Eiband, Dongheui Lee

{"title":"Identification of Common Force-based Robot Skills from the Human and Robot Perspective","authors":"Thomas Eiband, Dongheui Lee","doi":"10.1109/HUMANOIDS47582.2021.9555681","DOIUrl":"https://doi.org/10.1109/HUMANOIDS47582.2021.9555681","url":null,"abstract":"Learning from Demonstration (LfD) can significantly speed up the knowledge transfer from human to robot, which has been proven for relatively unconstrained actions such as pick and place. However, transferring contact or force-based skills (contact skills) to a robot is noticeably harder since force and position constraints need to be considered simultaneously. We propose a set of contact skills, which differ in the force and kinematic constraints. In a first user study, several subjects were asked to term a variety of force-based interactions, from which skill names were derived. In a second and third user study, the identified skill names are used to let a test group of subjects classify the shown interactions. To evaluate the skill recognition from the robot perspective, we propose a feature-based classification scheme to recognize such skills with a robotic system in a LfD setting. Our findings prove that humans are able to understand the meaning of the different skills and, using the classification pipeline, the robot is able to recognize the different skills from human demonstrations.","PeriodicalId":320510,"journal":{"name":"2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids)","volume":"16 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":"114635104","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