2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)最新文献_第8页

Comparing Human and Robot Performance in the Execution of Kitchen Tasks: Evaluating Grasping and Dexterous Manipulation Skills 比较人类和机器人在执行厨房任务中的表现:评估抓取和灵巧操作技能

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000248

Nathan Elangovan, Che-Ming Chang, Ricardo V. Godoy, Felipe Sanches, Kevin Wang, Patrick Jarvis, Minas Liarokapis

{"title":"Comparing Human and Robot Performance in the Execution of Kitchen Tasks: Evaluating Grasping and Dexterous Manipulation Skills","authors":"Nathan Elangovan, Che-Ming Chang, Ricardo V. Godoy, Felipe Sanches, Kevin Wang, Patrick Jarvis, Minas Liarokapis","doi":"10.1109/Humanoids53995.2022.10000248","DOIUrl":"https://doi.org/10.1109/Humanoids53995.2022.10000248","url":null,"abstract":"Over the last decades there has been a lot of research effort focusing on the development of household robots. Such robots need to execute a plethora of complex tasks that require significant dexterity and that need to be employed in dynamic and unstructured environments (e.g., a Kitchen environment). In this work, we focus on comparing human and robot performance in the execution of complex kitchen tasks, assessing the grasping and dexterous manipulation skills that are required. In particular, the study is based on a comprehensive collection of grasping and manipulation strategies that are employed by humans and humans directly operating robots. A dataset is created containing more than 2000 activities that are typically executed in a kitchen environment and a total of more than two hours of data. Based on the analysis of this dataset, we propose a taxonomy that classifies the attributes of kitchen specific grasping and manipulation strategies, as well as appropriate benchmarks to compare the performance of robotic grippers against human counterparts using what we call a dexterity/capability map. The color-coded maps enable us to visualize the current capabilities and limitations of robotic grippers in the execution of specific tasks. These insights can be used for the development of new classes of grippers and hands capable of performing on par with human hands.","PeriodicalId":180816,"journal":{"name":"2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128060540","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

HumanoidBot: Full-Body Humanoid Chitchat System HumanoidBot:全身人形聊天系统

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000209

Gabriel D. C. Seppelfelt, Tomoki Asaka, T. Nagai, Soh Yukizaki

引用次数: 1

Self-collision avoidance in bimanual teleoperation using CollisionIK: algorithm revision and usability experiment 基于CollisionIK的手动遥操作自避碰撞:算法修正与可用性实验

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000179

Luciano Angelini, Manuela Uliano, Angela Mazzeo, Mattia Penzotti, M. Controzzi

引用次数: 1

Whole-Body Control and Estimation of Humanoid Robots with Link Flexibility 具有关节柔性的仿人机器人全身控制与估计

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000157

Giulio Romualdi, N. Villa, Stefano Dafarra, D. Pucci, O. Stasse

{"title":"Whole-Body Control and Estimation of Humanoid Robots with Link Flexibility","authors":"Giulio Romualdi, N. Villa, Stefano Dafarra, D. Pucci, O. Stasse","doi":"10.1109/Humanoids53995.2022.10000157","DOIUrl":"https://doi.org/10.1109/Humanoids53995.2022.10000157","url":null,"abstract":"This article presents a whole-body controller for humanoid robots affected by concentrated link flexibility. We characterize the link flexibility by introducing passive joints at the concentration of deflections, which separate the flexible links into two or more rigid bodies. In this way, we extend our robot model to take link deflections into account as underactuated extra degrees of freedom, allowing us to design a whole-body controller capable to anticipate deformations. Since in a real scenario, the deflection is not directly measurable, we present an observer aiming at estimating the flexible joint state, namely position, velocity, and torque, only considering the measured contact force and the state of actuated joint. We validate the overall approach in simulations with the humanoid robot TALOS, whose hip is mechanically flexible due to a localized mechanical weakness. Furthermore, the paper compares the proposed whole-body control strategy with state-of-the-art approaches. Finally, we analyze the performance of the estimator in the case of different values of hip elasticity.","PeriodicalId":180816,"journal":{"name":"2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125477126","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: 1

Improving Sample Efficiency of Example-Guided Deep Reinforcement Learning for Bipedal Walking 提高两足步行示例引导深度强化学习的样本效率

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000068

R. Galljamov, Guoping Zhao, B. Belousov, A. Seyfarth, Jan Peters

引用次数: 0

Preliminary Design and Development of a Selectable Stiffness Joint for Elbow Orthosis 肘关节矫形器可选刚度关节的初步设计与研制

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000188

Robinson Guachi, Flavio Napoleoni, Francesco Pipitone, M. Controzzi

{"title":"Preliminary Design and Development of a Selectable Stiffness Joint for Elbow Orthosis","authors":"Robinson Guachi, Flavio Napoleoni, Francesco Pipitone, M. Controzzi","doi":"10.1109/Humanoids53995.2022.10000188","DOIUrl":"https://doi.org/10.1109/Humanoids53995.2022.10000188","url":null,"abstract":"The rehabilitation of a patient with a brachial plexus injury comprises of motor activities aimed at preventing muscular atrophy and fibrosis. Patients are frequently prescribed passive orthoses for shoulder and forearm support and muscle exercises using elastic bands as part of their functional treatment. Despite the clear need for assistive technology to help patients with upper extremity disability, research and development for upper extremity assistive technologies is not particularly prospering. In this scenario, developing an elbow orthosis that is compact, lightweight, and combines different functionalities customizable to the patient needs can maximizing the rehabilitation process. Here we show a new wearable passive elbow orthosis for the upper limb that has been designed to allow the output impedance of the joint to be modulated between three discrete modes depending on the user needs and motor task performed: free swing mode (1), allowing for the free flexion/extension of the elbow. Compliant mode (2), the elbow provides an elastic torque (customizable) opposed to the flexion/extension movements. Finally, the stiff mode (3) enables the patient to lock-hold the arm in a specific position. The alpha prototype has been developed, integrated and kinematic verified according to the technical specifications.","PeriodicalId":180816,"journal":{"name":"2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127147958","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

Force Feedback Control For Dexterous Robotic Hands Using Conditional Postural Synergies 基于条件姿势协同的灵巧机械手力反馈控制

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000162

D. Dimou, J. Santos-Victor, Plinio Moreno

引用次数: 0

NaivPhys4RP - Towards Human-like Robot Perception “Physical Reasoning based on Embodied Probabilistic Simulation” NaivPhys4RP -迈向类人机器人感知“基于具身概率模拟的物理推理”

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000153

Franklin Kenghagho, M. Neumann, Patrick Mania, Toni Tan, F. Siddiky, René Weller, G. Zachmann, M. Beetz

{"title":"NaivPhys4RP - Towards Human-like Robot Perception “Physical Reasoning based on Embodied Probabilistic Simulation”","authors":"Franklin Kenghagho, M. Neumann, Patrick Mania, Toni Tan, F. Siddiky, René Weller, G. Zachmann, M. Beetz","doi":"10.1109/Humanoids53995.2022.10000153","DOIUrl":"https://doi.org/10.1109/Humanoids53995.2022.10000153","url":null,"abstract":"Perception in complex environments especially dynamic and human-centered ones goes beyond classical tasks such as classification usually known as the what- and where-object-questions from sensor data, and poses at least three challenges that are missed by most and not properly addressed by some actual robot perception systems. Note that sensors are extrinsically (e.g., clutter, embodiedness-due noise, delayed processing) and intrinsically (e.g., depth of transparent objects) very limited, resulting in a lack of or high-entropy data, that can only be difficultly compressed during learning, difficultly explained or intensively processed during interpretation. (a) Therefore, the perception system should rather reason about the causes that produce such effects (how/why-happen-questions). (b) It should reason about the consequences (effects) of agent-object and object-object interactions in order to anticipate (what-happen-questions) the (e.g., undesired) world state and then enable successful action on time. (c) Finally, it should explain its outputs for safety (meta why/how-happen-questions). This paper introduces a novel white-box and causal generative model of robot perception (NaivPhys4RP) that emulates human perception by capturing the Big Five aspects (FPCIU)11Functionality, Physics, Causality, Intention, Utility of human commonsense, recently established, that invisibly (dark) drive our observational data and allow us to overcome the above problems. However, NaivPhys4RP particularly focuses on the aspect of physics, which ultimately and constructively determines the world state.","PeriodicalId":180816,"journal":{"name":"2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127966070","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

Multimodal reinforcement learning for partner specific adaptation in robot-multi-robot interaction 机器人-多机器人交互中伙伴特定适应的多模态强化学习

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000205

M. Kirtay, V. Hafner, M. Asada, A. Kuhlen, Erhan Öztop

{"title":"Multimodal reinforcement learning for partner specific adaptation in robot-multi-robot interaction","authors":"M. Kirtay, V. Hafner, M. Asada, A. Kuhlen, Erhan Öztop","doi":"10.1109/Humanoids53995.2022.10000205","DOIUrl":"https://doi.org/10.1109/Humanoids53995.2022.10000205","url":null,"abstract":"Successful and efficient teamwork requires knowledge of the individual team members' expertise. Such knowledge is typically acquired in social interaction and forms the basis for socially intelligent, partner-adapted behavior. This study aims to implement this ability in teams of multiple humanoid robots. To this end, a humanoid robot, Nao, interacted with three Pepper robots to perform a sequential audio-visual pattern recall task that required integrating multimodal information. Nao outsourced its decisions (i.e., action selections) to its robot partners to perform the task efficiently in terms of neural computational cost by applying reinforcement learning. During the interaction, Nao learned its partners' specific expertise, which allowed Nao to turn for guidance to the partner who has the expertise corresponding to the current task state. The cognitive processing of Nao included a multimodal auto-associative memory that allowed the determination of the cost of perceptual processing (i.e., cognitive load) when processing audio-visual stimuli. In turn, the processing cost is converted into a reward signal by an internal reward generation module. In this setting, the learner robot Nao aims to minimize cognitive load by turning to the partner whose expertise corresponds to a given task state. Overall, the results indicate that the learner robot discovers the expertise of partners and exploits this information to execute its task with low neural computational cost or cognitive load.","PeriodicalId":180816,"journal":{"name":"2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125720095","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

A Guideline for Humanoid Leg Design with Oblique Axes for Bipedal Locomotion 两足运动斜轴类人腿设计指南

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000126

Konrad Fründ, Anton Leonhard Shu, F. Loeffl, C. Ott

引用次数: 0