Robotics: Science and Systems XIX最新文献_第3页

Robust and Versatile Bipedal Jumping Control through Reinforcement Learning 基于强化学习的鲁棒多用途双足跳跃控制

Robotics: Science and Systems XIX Pub Date : 2023-02-19 DOI: 10.15607/RSS.2023.XIX.052

Zhongyu Li, X. B. Peng, P. Abbeel, S. Levine, G. Berseth, K. Sreenath

{"title":"Robust and Versatile Bipedal Jumping Control through Reinforcement Learning","authors":"Zhongyu Li, X. B. Peng, P. Abbeel, S. Levine, G. Berseth, K. Sreenath","doi":"10.15607/RSS.2023.XIX.052","DOIUrl":"https://doi.org/10.15607/RSS.2023.XIX.052","url":null,"abstract":"This work aims to push the limits of agility for bipedal robots by enabling a torque-controlled bipedal robot to perform robust and versatile dynamic jumps in the real world. We present a reinforcement learning framework for training a robot to accomplish a large variety of jumping tasks, such as jumping to different locations and directions. To improve performance on these challenging tasks, we develop a new policy structure that encodes the robot's long-term input/output (I/O) history while also providing direct access to a short-term I/O history. In order to train a versatile jumping policy, we utilize a multi-stage training scheme that includes different training stages for different objectives. After multi-stage training, the policy can be directly transferred to a real bipedal Cassie robot. Training on different tasks and exploring more diverse scenarios lead to highly robust policies that can exploit the diverse set of learned maneuvers to recover from perturbations or poor landings during real-world deployment. Such robustness in the proposed policy enables Cassie to succeed in completing a variety of challenging jump tasks in the real world, such as standing long jumps, jumping onto elevated platforms, and multi-axes jumps.","PeriodicalId":248720,"journal":{"name":"Robotics: Science and Systems XIX","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131497951","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

StructDiffusion: Language-Guided Creation of Physically-Valid Structures using Unseen Objects StructDiffusion:语言引导下使用看不见的对象创建物理有效的结构

Robotics: Science and Systems XIX Pub Date : 2022-11-08 DOI: 10.15607/RSS.2023.XIX.031

Weiyu Liu, Yilun Du, Tucker Hermans, S. Chernova, Chris Paxton

{"title":"StructDiffusion: Language-Guided Creation of Physically-Valid Structures using Unseen Objects","authors":"Weiyu Liu, Yilun Du, Tucker Hermans, S. Chernova, Chris Paxton","doi":"10.15607/RSS.2023.XIX.031","DOIUrl":"https://doi.org/10.15607/RSS.2023.XIX.031","url":null,"abstract":"Robots operating in human environments must be able to rearrange objects into semantically-meaningful configurations, even if these objects are previously unseen. In this work, we focus on the problem of building physically-valid structures without step-by-step instructions. We propose StructDiffusion, which combines a diffusion model and an object-centric transformer to construct structures given partial-view point clouds and high-level language goals, such as\"set the table\". Our method can perform multiple challenging language-conditioned multi-step 3D planning tasks using one model. StructDiffusion even improves the success rate of assembling physically-valid structures out of unseen objects by on average 16% over an existing multi-modal transformer model trained on specific structures. We show experiments on held-out objects in both simulation and on real-world rearrangement tasks. Importantly, we show how integrating both a diffusion model and a collision-discriminator model allows for improved generalization over other methods when rearranging previously-unseen objects. For videos and additional results, see our website: https://structdiffusion.github.io/.","PeriodicalId":248720,"journal":{"name":"Robotics: Science and Systems XIX","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128288018","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: 13

Self-Supervised Visuo-Tactile Pretraining to Locate and Follow Garment Features 定位和跟踪服装特征的自监督视觉-触觉预训练

Robotics: Science and Systems XIX Pub Date : 2022-09-26 DOI: 10.15607/RSS.2023.XIX.018

J. Kerr, Huang Huang, Albert Wilcox, Ryan Hoque, Jeffrey Ichnowski, R. Calandra, Ken Goldberg

{"title":"Self-Supervised Visuo-Tactile Pretraining to Locate and Follow Garment Features","authors":"J. Kerr, Huang Huang, Albert Wilcox, Ryan Hoque, Jeffrey Ichnowski, R. Calandra, Ken Goldberg","doi":"10.15607/RSS.2023.XIX.018","DOIUrl":"https://doi.org/10.15607/RSS.2023.XIX.018","url":null,"abstract":"Humans make extensive use of vision and touch as complementary senses, with vision providing global information about the scene and touch measuring local information during manipulation without suffering from occlusions. While prior work demonstrates the efficacy of tactile sensing for precise manipulation of deformables, they typically rely on supervised, human-labeled datasets. We propose Self-Supervised Visuo-Tactile Pretraining (SSVTP), a framework for learning multi-task visuo-tactile representations in a self-supervised manner through cross-modal supervision. We design a mechanism that enables a robot to autonomously collect precisely spatially-aligned visual and tactile image pairs, then train visual and tactile encoders to embed these pairs into a shared latent space using cross-modal contrastive loss. We apply this latent space to downstream perception and control of deformable garments on flat surfaces, and evaluate the flexibility of the learned representations without fine-tuning on 5 tasks: feature classification, contact localization, anomaly detection, feature search from a visual query (e.g., garment feature localization under occlusion), and edge following along cloth edges. The pretrained representations achieve a 73-100% success rate on these 5 tasks.","PeriodicalId":248720,"journal":{"name":"Robotics: Science and Systems XIX","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115615500","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

Demonstrating RFUniverse: A Multiphysics Simulation Platform for Embodied AI 演示RFUniverse:嵌入式AI的多物理场仿真平台

Robotics: Science and Systems XIX Pub Date : 2022-02-01 DOI: 10.15607/RSS.2023.XIX.087

Haoyuan Fu, Wenqiang Xu, Ruolin Ye, Han Xue, Zhenjun Yu, Tutian Tang, Yutong Li, Wenxin Du, Jieyi Zhang, Cewu Lu

{"title":"Demonstrating RFUniverse: A Multiphysics Simulation Platform for Embodied AI","authors":"Haoyuan Fu, Wenqiang Xu, Ruolin Ye, Han Xue, Zhenjun Yu, Tutian Tang, Yutong Li, Wenxin Du, Jieyi Zhang, Cewu Lu","doi":"10.15607/RSS.2023.XIX.087","DOIUrl":"https://doi.org/10.15607/RSS.2023.XIX.087","url":null,"abstract":"Multiphysics phenomena, the coupling effects involving different aspects of physics laws, are pervasive in the real world and can often be encountered when performing everyday household tasks. Intelligent agents which seek to assist or replace human laborers will need to learn to cope with such phenomena in household task settings. To equip the agents with such kind of abilities, the research community needs a simulation environment, which will have the capability to serve as the testbed for the training process of these intelligent agents, to have the ability to support multiphysics coupling effects. Though many mature simulation software for multiphysics simulation have been adopted in industrial production, such techniques have not been applied to robot learning or embodied AI research. To bridge the gap, we propose a novel simulation environment named RFUniverse. This simulator can not only compute rigid and multi-body dynamics, but also multiphysics coupling effects commonly observed in daily life, such as air-solid interaction, fluid-solid interaction, and heat transfer. Because of the unique multiphysics capacities of this simulator, we can benchmark tasks that involve complex dynamics due to multiphysics coupling effects in a simulation environment before deploying to the real world. RFUniverse provides multiple interfaces to let the users interact with the virtual world in various ways, which is helpful and essential for learning, planning, and control. We benchmark three tasks with reinforcement learning, including food cutting, water pushing, and towel catching. We also evaluate butter pushing with a classic planning-control paradigm. This simulator offers an enhancement of physics simulation in terms of the computation of multiphysics coupling effects.","PeriodicalId":248720,"journal":{"name":"Robotics: Science and Systems XIX","volume":"27 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129407054","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