2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids)最新文献_第6页

Weakly-Supervised Object Detection Learning through Human-Robot Interaction 基于人机交互的弱监督目标检测学习

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2021-07-16 DOI: 10.1109/HUMANOIDS47582.2021.9555781

Elisa Maiettini, V. Tikhanoff, L. Natale

{"title":"Weakly-Supervised Object Detection Learning through Human-Robot Interaction","authors":"Elisa Maiettini, V. Tikhanoff, L. Natale","doi":"10.1109/HUMANOIDS47582.2021.9555781","DOIUrl":"https://doi.org/10.1109/HUMANOIDS47582.2021.9555781","url":null,"abstract":"Reliable perception and efficient adaptation to novel conditions are priority skills for humanoids that function in dynamic environments. The vast advancements in latest computer vision research, brought by deep learning methods, are appealing for the robotics community. However, their adoption in applied domains is not straightforward since adapting them to new tasks is strongly demanding in terms of annotated data and optimization time. Nevertheless, robotic platforms, and especially humanoids, present opportunities (such as additional sensors and the chance to explore the environment) that can be exploited to overcome these issues.In this paper, we present a pipeline for efficiently training an object detection system on a humanoid robot. The proposed system allows to iteratively adapt an object detection model to novel scenarios, by exploiting: (i) a teacher-learner pipeline, (ii) weakly supervised learning techniques to reduce the human labeling effort and (iii) an on-line learning approach for fast model re-training. We use the R1 humanoid robot for both testing the proposed pipeline in a real-time application and acquire sequences of images to benchmark the method. We made the code of the application publicly available.","PeriodicalId":320510,"journal":{"name":"2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130307102","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

Optimization-Based Quadrupedal Hybrid Wheeled-Legged Locomotion 基于优化的四足轮腿混合运动

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2021-07-15 DOI: 10.1109/HUMANOIDS47582.2021.9555780

Italo Belli, Matteo Parigi Polverini, Arturo Laurenzi, E. Hoffman, P. Rocco, N. Tsagarakis

引用次数: 4

The MIT Humanoid Robot: Design, Motion Planning, and Control For Acrobatic Behaviors 麻省理工学院人形机器人:设计、运动规划和杂技行为控制

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2021-04-19 DOI: 10.1109/HUMANOIDS47582.2021.9555782

Matthew Chignoli, Donghyun Kim, Elijah Stanger-Jones, Sangbae Kim

{"title":"The MIT Humanoid Robot: Design, Motion Planning, and Control For Acrobatic Behaviors","authors":"Matthew Chignoli, Donghyun Kim, Elijah Stanger-Jones, Sangbae Kim","doi":"10.1109/HUMANOIDS47582.2021.9555782","DOIUrl":"https://doi.org/10.1109/HUMANOIDS47582.2021.9555782","url":null,"abstract":"Demonstrating acrobatic behavior of a humanoid robot such as flips and spinning jumps requires systematic approaches across hardware design, motion planning, and control. In this paper, we present a new humanoid robot design, an actuator-aware kino-dynamic motion planner, and a landing controller as part of a practical system design for highly dynamic motion control of the humanoid robot. To achieve the impulsive motions, we develop two new proprioceptive actuators. The actuator’s torque, velocity, and power limits are reflected in our kino-dynamic motion planner by approximating the configuration-dependent reaction force limits. For the landing control, we effectively integrate model-predictive control and whole-body impulse control by connecting them in a dynamically consistent way to accomplish both the long-time horizon optimal control and high-bandwidth full-body dynamics-based feedback. With the carefully designed hardware and control framework, we successfully demonstrate dynamic behaviors such as back flips, front flips, and spinning jumps in our realistic dynamics simulation.","PeriodicalId":320510,"journal":{"name":"2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids)","volume":"312 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125542859","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: 62

Policy Decomposition: Approximate Optimal Control with Suboptimality Estimates 策略分解:具有次最优估计的近似最优控制

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2021-03-03 DOI: 10.1109/HUMANOIDS47582.2021.9555796

Ashwin Khadke, H. Geyer

{"title":"Policy Decomposition: Approximate Optimal Control with Suboptimality Estimates","authors":"Ashwin Khadke, H. Geyer","doi":"10.1109/HUMANOIDS47582.2021.9555796","DOIUrl":"https://doi.org/10.1109/HUMANOIDS47582.2021.9555796","url":null,"abstract":"Numerically computing global policies to optimal control problems for complex dynamical systems is mostly intractable. In consequence, a number of approximation methods have been developed. However, none of the current methods can quantify how much the resulting control underperforms the elusive globally optimal solution. Here we propose policy decomposition, an approximation method with explicit suboptimality estimates. Our method decomposes the optimal control problem into lower-dimensional subproblems, whose optimal solutions are recombined to build a control policy for the entire system. Many such combinations exist, and we introduce the value error and its LQR and DDP estimates to predict the suboptimality of possible combinations and prioritize the ones that minimize it. Using a cart-pole, a 3-link balancing biped and N-link planar manipulators as example systems, we find that the estimates correctly identify the best combinations, yielding control policies in a fraction of the time it takes to compute the optimal control without a notable sacrifice in closed-loop performance. While more research will be needed to find ways of dealing with the combinatorics of policy decomposition, the results suggest this method could be an effective alternative for approximating optimal control in intractable systems.","PeriodicalId":320510,"journal":{"name":"2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids)","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134478972","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

Design, analysis and control of the series-parallel hybrid RH5 humanoid robot 串并联混联RH5类人机器人的设计、分析与控制

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2021-01-26 DOI: 10.1109/HUMANOIDS47582.2021.9555770

Julian Eßer, Shivesh Kumar, Heiner Peters, Vinzenz Bargsten, J. Gea, Carlos Mastalli, O. Stasse, F. Kirchner

引用次数: 12

Open-Ended Fine-Grained 3D Object Categorization by Combining Shape and Texture Features in Multiple Colorspaces 在多个颜色空间中结合形状和纹理特征的开放式细粒度3D对象分类

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2020-09-19 DOI: 10.1109/HUMANOIDS47582.2021.9555670

Nils Keunecke, S. Kasaei

{"title":"Open-Ended Fine-Grained 3D Object Categorization by Combining Shape and Texture Features in Multiple Colorspaces","authors":"Nils Keunecke, S. Kasaei","doi":"10.1109/HUMANOIDS47582.2021.9555670","DOIUrl":"https://doi.org/10.1109/HUMANOIDS47582.2021.9555670","url":null,"abstract":"As a consequence of an ever-increasing number of service robots, there is a growing demand for highly accurate real-time 3D object recognition. Considering the expansion of robot applications in more complex and dynamic environments, it is evident that it is not possible to pre-program all object categories and anticipate all exceptions in advance. Therefore, robots should have the functionality to learn about new object categories in an open-ended fashion while working in the environment. Towards this goal, we propose a deep transfer learning approach to generate a scale- and pose-invariant object representation by considering shape and texture information in multiple color spaces. The obtained global object representation is then fed to an instance-based object category learning and recognition, where a non-expert human user exists in the learning loop and can interactively guide the process of experience acquisition by teaching new object categories, or by correcting insufficient or erroneous categories. In this work, shape information encodes the common patterns of all categories, while texture information is used to describes the appearance of each instance in detail. Multiple color space combinations and network architectures are evaluated to find the most descriptive system. Experimental results showed that the proposed network architecture outperformed the selected state-of-the-art in terms of object classification accuracy and scalability. Furthermore, we performed a real robot experiment in the context of serve_a_beer scenario to show the real-time performance of the proposed approach.","PeriodicalId":320510,"journal":{"name":"2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids)","volume":"53 17","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113938961","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

Stochastic and Robust MPC for Bipedal Locomotion: A Comparative Study on Robustness and Performance 双足运动的随机和鲁棒MPC:鲁棒性和性能的比较研究

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2020-05-15 DOI: 10.1109/HUMANOIDS47582.2021.9555783

Ahmad Gazar, M. Khadiv, A. Prete, L. Righetti

引用次数: 15

Human to Robot Whole-Body Motion Transfer 人到机器人的全身运动传递

2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids) Pub Date : 2019-09-13 DOI: 10.1109/HUMANOIDS47582.2021.9555769

Miguel Arduengo, Ana Arduengo, Adrià Colomé, J. Lobo-Prat, C. Torras

{"title":"Human to Robot Whole-Body Motion Transfer","authors":"Miguel Arduengo, Ana Arduengo, Adrià Colomé, J. Lobo-Prat, C. Torras","doi":"10.1109/HUMANOIDS47582.2021.9555769","DOIUrl":"https://doi.org/10.1109/HUMANOIDS47582.2021.9555769","url":null,"abstract":"Transferring human motion to a mobile robotic manipulator and ensuring safe physical human-robot interaction are crucial steps towards automating complex manipulation tasks in human-shared environments. In this work, we present a novel human to robot whole-body motion transfer framework. We propose a general solution to the correspondence problem, namely a mapping between the observed human posture and the robot one. For achieving real-time imitation and effective redundancy resolution, we use the whole-body control paradigm, proposing a specific task hierarchy, and present a differential drive control algorithm for the wheeled robot base. To ensure safe physical human-robot interaction, we propose a novel variable admittance controller that stably adapts the dynamics of the end-effector to switch between stiff and compliant behaviors. We validate our approach through several real-world experiments with the TIAGo robot. Results show effective real-time imitation and dynamic behavior adaptation. This constitutes an easy way for a non-expert to transfer a manipulation skill to an assistive robot.","PeriodicalId":320510,"journal":{"name":"2020 IEEE-RAS 20th International Conference on Humanoid Robots (Humanoids)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126070267","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