2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)最新文献_第9页

Online Human Intention Detection through Machine-learning based Algorithm for the Control of Lower-limbs Wearable Robot 基于机器学习的在线人意图检测算法在下肢可穿戴机器人控制中的应用

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000150

Huiseok Moon, Abderrahmane Boubezoul, L. Oukhellou, Y. Amirat, S. Mohammed

{"title":"Online Human Intention Detection through Machine-learning based Algorithm for the Control of Lower-limbs Wearable Robot","authors":"Huiseok Moon, Abderrahmane Boubezoul, L. Oukhellou, Y. Amirat, S. Mohammed","doi":"10.1109/Humanoids53995.2022.10000150","DOIUrl":"https://doi.org/10.1109/Humanoids53995.2022.10000150","url":null,"abstract":"Online human intention detection is one of the main challenges to ensure smooth human robot interaction for assistive robotics through wearable devices. This paper proposes a framework that combines both machine learning based algorithms and task-oriented control of an actuated-ankle-foot orthosis for human locomotion assistance during five gait modes that are level walking, stairs ascent/descent, and ramp ascent/descent. A random-forest based algorithm has been trained to provide an online classification of the five gait modes using kinematic features of a dataset collected with ten healthy subjects. Finally, appropriate assistive torques were applied at the ankle joint level with respect to the detected gait mode. The proposed scheme is verified in terms of gait mode detection success rate and the torque assistance through the actuated-ankle-foot orthosis at the ankle joint level. One healthy subject participated in the experiments with and without applying the torque assistance strategy. The results show the following average success rates of 99.49%, 98.30%, 96.07%, 84.63%, and 85.55% for the different locomotion modes, that are level walking, stair ascent, stair descent, ramp ascent, and ramp descent, respectively.","PeriodicalId":180816,"journal":{"name":"2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)","volume":"166 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":"132168702","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 study on the benefits of using variable stiffness feet for humanoid walking on rough terrains 在崎岖地形上使用变刚度足对仿人行走的益处研究

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000240

Irene Frizza, Hiroshi Kaminaga, K. Ayusawa, P. Fraisse, G. Venture

{"title":"A study on the benefits of using variable stiffness feet for humanoid walking on rough terrains","authors":"Irene Frizza, Hiroshi Kaminaga, K. Ayusawa, P. Fraisse, G. Venture","doi":"10.1109/Humanoids53995.2022.10000240","DOIUrl":"https://doi.org/10.1109/Humanoids53995.2022.10000240","url":null,"abstract":"This work aims to study the effects of the variable stiffness of a compliant foot on humanoid locomotion performance. Through dynamical simulations, we demonstrate that the introduction of the variable stiffness feet, changing in conjunction with the ground roughness significantly improves the walking performance on different types of rough terrain of a humanoid robot. We propose a compliant foot model with multiple viscoelastic elements in the sole. We optimize the sole stiffness for different types of uneven terrains: with rocks, tiles, and obstacles of different shapes and dimensions. We implement a variable stiffness method according to the ground roughness during the walking. Furthermore, the timing of ground scanning and optimal stiffness estimation throw the k-nearest neighbors (KNN) algorithm is described. The comparison of the results obtained with completely flat sole, compliant sole with fixed stiffness, and compliant sole with variable stiffness show the superiority of the variable stiffness feet over the two others. Finally, we present some limitations of the flexible robotic foot in the dynamic simulation.","PeriodicalId":180816,"journal":{"name":"2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)","volume":"60 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":"132182447","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

RoverNet: Vision-Based Adaptive Human-to-Robot Object Handovers RoverNet:基于视觉的自适应人机对象切换

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000200

Matija Mavsar, A. Ude

引用次数: 1

Gait cycle modeling in cerebral palsy condition 脑瘫患者步态周期建模

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.9999744

Sabrina Otmani, G. Michon, B. Watier

引用次数: 0

Target-Referred DMPs for Learning Bimanual Tasks from Shared-Autonomy Telemanipulation 共享自主远程操作中学习手工任务的目标参考dmp

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000233

Fabio Amadio, Marco Laghi, Luigi Raiano, Federico Rollo, Andrea Zunino, G. Raiola, A. Ajoudani

{"title":"Target-Referred DMPs for Learning Bimanual Tasks from Shared-Autonomy Telemanipulation","authors":"Fabio Amadio, Marco Laghi, Luigi Raiano, Federico Rollo, Andrea Zunino, G. Raiola, A. Ajoudani","doi":"10.1109/Humanoids53995.2022.10000233","DOIUrl":"https://doi.org/10.1109/Humanoids53995.2022.10000233","url":null,"abstract":"The Learning from Demonstration (LfD) paradigm allows transferring human skills to robots without the need for explicit programming. To be effective, it requires: (i) a learning technique able to encode and adapt demonstrated skills to different contexts and (ii) an intuitive user interface for task demonstrations. Both aspects become more crucial when dealing with multi-robot coordination. Dynamic Movement Primitives (DMPs) are among the most reliable LfD techniques. However, they might struggle to correctly replicate learned manipulation tasks for a target object with a different orientation from the demonstration. On the user side, telemanipulation solutions can provide an effective interface for demonstration acquisition. Recent shared-autonomy control strategies allow intuitive coordination of multi-robot platforms, but none has been exploited in LfD. In this work, we propose a novel implementation of DMPs, called Target-Referred DMP (TR-DMP), which improves generalization capacities and overcomes the above limitation. Furthermore, we show how to embed a shared-autonomy tele-manipulation strategy in our LfD architecture for an intuitive training and execution of bimanual coordinated tasks. The improved performance is proven through two real case studies.","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":"131242815","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

Task-grasping from a demonstrated human strategy 从演示的人类策略中掌握任务

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000167

Daichi Saito, Kazuhiro Sasabuchi, Naoki Wake, J. Takamatsu, H. Koike, K. Ikeuchi

{"title":"Task-grasping from a demonstrated human strategy","authors":"Daichi Saito, Kazuhiro Sasabuchi, Naoki Wake, J. Takamatsu, H. Koike, K. Ikeuchi","doi":"10.1109/Humanoids53995.2022.10000167","DOIUrl":"https://doi.org/10.1109/Humanoids53995.2022.10000167","url":null,"abstract":"Task-grasping is a challenge in robot grasping because a higher-level understanding of the entire task-context is required for performing the grasp. Learning-from-observation (LfO) is a framework for robot teaching, where a demonstrator teaches manipulative operations as well as contexts. To utilize the LfO approach for the task-grasping problem, we classified grasps based on the force-exertion required in a subsequent task. The classification based on force-exertion was defined by observing grasps from both the human-end perspective and the robot-end perspective, and a lazy-closure was newly defined as one of the types. We demonstrated that one general policy per force-exertion-type is sufficient for handling different grasp shapes. Experimental results show that the appropriate grasp for a task sequence can be executed by obtaining the force-exertion-type from a one-shot human demonstration and then by executing the exertion policy. Real-robot execution results are shown in two task sequence scenarios: (1) picking up a cup and placing it right side up in a basket and (2) opening a refrigerator.","PeriodicalId":180816,"journal":{"name":"2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)","volume":"97 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":"134346470","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: 5

Data-Driven Safety Verification and Explainability for Whole-Body Manipulation and Locomotion 数据驱动的全身操作和运动的安全性验证和可解释性

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000221

Junhyeok Ahn, S. Bang, Carlos Gonzalez, Yuanchen Yuan, L. Sentis

{"title":"Data-Driven Safety Verification and Explainability for Whole-Body Manipulation and Locomotion","authors":"Junhyeok Ahn, S. Bang, Carlos Gonzalez, Yuanchen Yuan, L. Sentis","doi":"10.1109/Humanoids53995.2022.10000221","DOIUrl":"https://doi.org/10.1109/Humanoids53995.2022.10000221","url":null,"abstract":"Planning safe motions for legged robots requires sophisticated safety verification tools. However, designing such tools for such complex systems is challenging due to the nonlinear and high-dimensional nature of these systems' dynamics. In this paper, we present a probabilistic verification framework for legged systems, which evaluates the safety of planned trajectories by learning an assessment function from trajectories collected from a closed-loop system. Our approach does not require an analytic expression of the closed-loop dynamics, thus enabling safety verification of systems with complex models and controllers. Our framework consists of an offline stage that initializes a safety assessment function by simulating a nominal model and an online stage that adapts the function to address the sim-to-real gap. The performance of the proposed approach for safety verification is demonstrated using a quadruped balancing task and a humanoid reaching task. The results demonstrate that our framework accurately predicts the systems' safety both at the planning phase to generate robust trajectories and at execution phase to detect unexpected external disturbances.","PeriodicalId":180816,"journal":{"name":"2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)","volume":"9 4 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":"117275640","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

Robust Analysis for Mechanism and Behavior Co-optimization of High-performance Legged Robots 高性能腿式机器人机构与行为协同优化的鲁棒分析

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.9999745

Antonios E. Gkikakis, R. Featherstone

引用次数: 1

Human Inspired Grip-Release Technique for Robot-Human Handovers 机器人-人类交接的人类启发握力-释放技术

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000227

P. Khanna, Mårten Björkman, Christian Smith

引用次数: 7

Learning-Based Wiping Behavior of Low-Rigidity Robots Considering Various Surface Materials and Task Definitions 考虑不同表面材料和任务定义的低刚度机器人基于学习的擦拭行为

2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids) Pub Date : 2022-11-28 DOI: 10.1109/Humanoids53995.2022.10000172

Kento Kawaharazuka, Naoaki Kanazawa, K. Okada, M. Inaba

{"title":"Learning-Based Wiping Behavior of Low-Rigidity Robots Considering Various Surface Materials and Task Definitions","authors":"Kento Kawaharazuka, Naoaki Kanazawa, K. Okada, M. Inaba","doi":"10.1109/Humanoids53995.2022.10000172","DOIUrl":"https://doi.org/10.1109/Humanoids53995.2022.10000172","url":null,"abstract":"Wiping behavior is a task of tracing the surface of an object while feeling the force with the palm of the hand. It is necessary to adjust the force and posture appropriately considering the various contact conditions felt by the hand. Several studies have been conducted on the wiping motion, however, these studies have only dealt with a single surface material, and have only considered the application of the amount of appropriate force, lacking intelligent movements to ensure that the force is applied either evenly to the entire surface or to a certain area. Depending on the surface material, the hand posture and pressing force should be varied appropriately, and this is highly dependent on the definition of the task. Also, most of the movements are executed by high-rigidity robots that are easy to model, and few movements are executed by robots that are low-rigidity but therefore have a small risk of damage due to excessive contact. So, in this study, we develop a method of motion generation based on the learned prediction of contact force during the wiping motion of a low-rigidity robot. We show that MyCobot, which is made of low-rigidity resin, can appropriately perform wiping behaviors on a plane with multiple surface materials based on various task definitions.","PeriodicalId":180816,"journal":{"name":"2022 IEEE-RAS 21st International Conference on Humanoid Robots (Humanoids)","volume":"24 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":"116350656","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