arXiv - CS - Robotics最新文献_第7页

AnySkin: Plug-and-play Skin Sensing for Robotic Touch AnySkin：用于机器人触摸的即插即用皮肤传感技术

arXiv - CS - Robotics Pub Date : 2024-09-12 DOI: arxiv-2409.08276

Raunaq Bhirangi, Venkatesh Pattabiraman, Enes Erciyes, Yifeng Cao, Tess Hellebrekers, Lerrel Pinto

{"title":"AnySkin: Plug-and-play Skin Sensing for Robotic Touch","authors":"Raunaq Bhirangi, Venkatesh Pattabiraman, Enes Erciyes, Yifeng Cao, Tess Hellebrekers, Lerrel Pinto","doi":"arxiv-2409.08276","DOIUrl":"https://doi.org/arxiv-2409.08276","url":null,"abstract":"While tactile sensing is widely accepted as an important and useful sensing\u0000modality, its use pales in comparison to other sensory modalities like vision\u0000and proprioception. AnySkin addresses the critical challenges that impede the\u0000use of tactile sensing -- versatility, replaceability, and data reusability.\u0000Building on the simplistic design of ReSkin, and decoupling the sensing\u0000electronics from the sensing interface, AnySkin simplifies integration making\u0000it as straightforward as putting on a phone case and connecting a charger.\u0000Furthermore, AnySkin is the first uncalibrated tactile-sensor with\u0000cross-instance generalizability of learned manipulation policies. To summarize,\u0000this work makes three key contributions: first, we introduce a streamlined\u0000fabrication process and a design tool for creating an adhesive-free, durable\u0000and easily replaceable magnetic tactile sensor; second, we characterize slip\u0000detection and policy learning with the AnySkin sensor; and third, we\u0000demonstrate zero-shot generalization of models trained on one instance of\u0000AnySkin to new instances, and compare it with popular existing tactile\u0000solutions like DIGIT and ReSkin.https://any-skin.github.io/","PeriodicalId":501031,"journal":{"name":"arXiv - CS - Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142222087","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

MosquitoMiner: A Light Weight Rover for Detecting and Eliminating Mosquito Breeding Sites MosquitoMiner：用于探测和消除蚊子繁殖地的轻型漫游车

arXiv - CS - Robotics Pub Date : 2024-09-12 DOI: arxiv-2409.08078

Md. Adnanul Islam, Md. Faiyaz Abdullah Sayeedi, Jannatul Ferdous Deepti, Shahanur Rahman Bappy, Safrin Sanzida Islam, Fahim Hafiz

{"title":"MosquitoMiner: A Light Weight Rover for Detecting and Eliminating Mosquito Breeding Sites","authors":"Md. Adnanul Islam, Md. Faiyaz Abdullah Sayeedi, Jannatul Ferdous Deepti, Shahanur Rahman Bappy, Safrin Sanzida Islam, Fahim Hafiz","doi":"arxiv-2409.08078","DOIUrl":"https://doi.org/arxiv-2409.08078","url":null,"abstract":"In this paper, we present a novel approach to the development and deployment\u0000of an autonomous mosquito breeding place detector rover with the object and\u0000obstacle detection capabilities to control mosquitoes. Mosquito-borne diseases\u0000continue to pose significant health threats globally, with conventional control\u0000methods proving slow and inefficient. Amidst rising concerns over the rapid\u0000spread of these diseases, there is an urgent need for innovative and efficient\u0000strategies to manage mosquito populations and prevent disease transmission. To\u0000mitigate the limitations of manual labor and traditional methods, our rover\u0000employs autonomous control strategies. Leveraging our own custom dataset, the\u0000rover can autonomously navigate along a pre-defined path, identifying and\u0000mitigating potential breeding grounds with precision. It then proceeds to\u0000eliminate these breeding grounds by spraying a chemical agent, effectively\u0000eradicating mosquito habitats. Our project demonstrates the effectiveness that\u0000is absent in traditional ways of controlling and safeguarding public health.\u0000The code for this project is available on GitHub at -\u0000https://github.com/faiyazabdullah/MosquitoMiner","PeriodicalId":501031,"journal":{"name":"arXiv - CS - Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142222094","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

Collaborating for Success: Optimizing System Efficiency and Resilience Under Agile Industrial Settings 合作共赢：在灵活的工业环境下优化系统效率和复原力

arXiv - CS - Robotics Pub Date : 2024-09-12 DOI: arxiv-2409.08166

Sunny Katyara, Suchita Sharma, Praveen Damacharla, Carlos Garcia Santiago, Francis O'Farrell, Philip Long

{"title":"Collaborating for Success: Optimizing System Efficiency and Resilience Under Agile Industrial Settings","authors":"Sunny Katyara, Suchita Sharma, Praveen Damacharla, Carlos Garcia Santiago, Francis O'Farrell, Philip Long","doi":"arxiv-2409.08166","DOIUrl":"https://doi.org/arxiv-2409.08166","url":null,"abstract":"Designing an efficient and resilient human-robot collaboration strategy that\u0000not only upholds the safety and ergonomics of shared workspace but also\u0000enhances the performance and agility of collaborative setup presents\u0000significant challenges concerning environment perception and robot control. In\u0000this research, we introduce a novel approach for collaborative environment\u0000monitoring and robot motion regulation to address this multifaceted problem.\u0000Our study proposes novel computation and division of safety monitoring zones,\u0000adhering to ISO 13855 and TS 15066 standards, utilizing 2D lasers information.\u0000These zones are not only configured in the standard three-layer arrangement but\u0000are also expanded into two adjacent quadrants, thereby enhancing system uptime\u0000and preventing unnecessary deadlocks. Moreover, we also leverage 3D visual\u0000information to track dynamic human articulations and extended intrusions.\u0000Drawing upon the fused sensory data from 2D and 3D perceptual spaces, our\u0000proposed hierarchical controller stably regulates robot velocity, validated\u0000using Lasalle in-variance principle. Empirical evaluations demonstrate that our\u0000approach significantly reduces task execution time and system response delay,\u0000resulting in improved efficiency and resilience within collaborative settings.","PeriodicalId":501031,"journal":{"name":"arXiv - CS - Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142222093","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

The Design of Informative Take-Over Requests for Semi-Autonomous Cyber-Physical Systems: Combining Spoken Language and Visual Icons in a Drone-Controller Setting 为半自主网络物理系统设计知情接管请求：在无人机控制器环境中结合口语和视觉图标

arXiv - CS - Robotics Pub Date : 2024-09-12 DOI: arxiv-2409.08253

Ashwini Gundappa, Emilia Ellsiepen, Lukas Schmitz, Frederik Wiehr, Vera Demberg

{"title":"The Design of Informative Take-Over Requests for Semi-Autonomous Cyber-Physical Systems: Combining Spoken Language and Visual Icons in a Drone-Controller Setting","authors":"Ashwini Gundappa, Emilia Ellsiepen, Lukas Schmitz, Frederik Wiehr, Vera Demberg","doi":"arxiv-2409.08253","DOIUrl":"https://doi.org/arxiv-2409.08253","url":null,"abstract":"The question of how cyber-physical systems should interact with human\u0000partners that can take over control or exert oversight is becoming more\u0000pressing, as these systems are deployed for an ever larger range of tasks.\u0000Drawing on the literatures on handing over control during semi-autonomous\u0000driving and human-robot interaction, we propose a design of a take-over request\u0000that combines an abstract pre-alert with an informative TOR: Relevant sensor\u0000information is highlighted on the controller's display, while a spoken message\u0000verbalizes the reason for the TOR. We conduct our study in the context of a\u0000semi-autonomous drone control scenario as our testbed. The goal of our online\u0000study is to assess in more detail what form a language-based TOR should take.\u0000Specifically, we compare a full sentence condition to shorter fragments, and\u0000test whether the visual highlighting should be done synchronously or\u0000asynchronously with the speech. Participants showed a higher accuracy in\u0000choosing the correct solution with our bi-modal TOR and felt that they were\u0000better able to recognize the critical situation. Using only fragments in the\u0000spoken message rather than full sentences did not lead to improved accuracy or\u0000faster reactions. Also, synchronizing the visual highlighting with the spoken\u0000message did not result in better accuracy and response times were even\u0000increased in this condition.","PeriodicalId":501031,"journal":{"name":"arXiv - CS - Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142222121","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

Q-value Regularized Decision ConvFormer for Offline Reinforcement Learning 用于离线强化学习的 Q 值正则化决策 ConvFormer

arXiv - CS - Robotics Pub Date : 2024-09-12 DOI: arxiv-2409.08062

Teng Yan, Zhendong Ruan, Yaobang Cai, Yu Han, Wenxian Li, Yang Zhang

{"title":"Q-value Regularized Decision ConvFormer for Offline Reinforcement Learning","authors":"Teng Yan, Zhendong Ruan, Yaobang Cai, Yu Han, Wenxian Li, Yang Zhang","doi":"arxiv-2409.08062","DOIUrl":"https://doi.org/arxiv-2409.08062","url":null,"abstract":"As a data-driven paradigm, offline reinforcement learning (Offline RL) has\u0000been formulated as sequence modeling, where the Decision Transformer (DT) has\u0000demonstrated exceptional capabilities. Unlike previous reinforcement learning\u0000methods that fit value functions or compute policy gradients, DT adjusts the\u0000autoregressive model based on the expected returns, past states, and actions,\u0000using a causally masked Transformer to output the optimal action. However, due\u0000to the inconsistency between the sampled returns within a single trajectory and\u0000the optimal returns across multiple trajectories, it is challenging to set an\u0000expected return to output the optimal action and stitch together suboptimal\u0000trajectories. Decision ConvFormer (DC) is easier to understand in the context\u0000of modeling RL trajectories within a Markov Decision Process compared to DT. We\u0000propose the Q-value Regularized Decision ConvFormer (QDC), which combines the\u0000understanding of RL trajectories by DC and incorporates a term that maximizes\u0000action values using dynamic programming methods during training. This ensures\u0000that the expected returns of the sampled actions are consistent with the\u0000optimal returns. QDC achieves excellent performance on the D4RL benchmark,\u0000outperforming or approaching the optimal level in all tested environments. It\u0000particularly demonstrates outstanding competitiveness in trajectory stitching\u0000capability.","PeriodicalId":501031,"journal":{"name":"arXiv - CS - Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142222124","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

Learning Skateboarding for Humanoid Robots through Massively Parallel Reinforcement Learning 通过大规模并行强化学习为仿人机器人学习滑板运动

arXiv - CS - Robotics Pub Date : 2024-09-12 DOI: arxiv-2409.07846

William Thibault, Vidyasagar Rajendran, William Melek, Katja Mombaur

引用次数: 0

Touch2Touch: Cross-Modal Tactile Generation for Object Manipulation Touch2Touch：用于物体操作的跨模式触觉生成

arXiv - CS - Robotics Pub Date : 2024-09-12 DOI: arxiv-2409.08269

Samanta Rodriguez, Yiming Dou, Miquel Oller, Andrew Owens, Nima Fazeli

引用次数: 0

Characterization and Design of A Hollow Cylindrical Ultrasonic Motor 中空圆柱形超声波电机的特性分析与设计

arXiv - CS - Robotics Pub Date : 2024-09-12 DOI: arxiv-2409.07690

Zhanyue Zhao, Yang Wang, Charles Bales, Daniel Ruiz-Cadalso, Howard Zheng, Cosme Furlong-Vazquez, Gregory Fischer

引用次数: 0

A three-dimensional force estimation method for the cable-driven soft robot based on monocular images 基于单目图像的缆索驱动软体机器人三维力估算方法

arXiv - CS - Robotics Pub Date : 2024-09-12 DOI: arxiv-2409.08033

Xiaohan Zhu, Ran Bu, Zhen Li, Fan Xu, Hesheng Wang

{"title":"A three-dimensional force estimation method for the cable-driven soft robot based on monocular images","authors":"Xiaohan Zhu, Ran Bu, Zhen Li, Fan Xu, Hesheng Wang","doi":"arxiv-2409.08033","DOIUrl":"https://doi.org/arxiv-2409.08033","url":null,"abstract":"Soft manipulators are known for their superiority in coping with\u0000high-safety-demanding interaction tasks, e.g., robot-assisted surgeries,\u0000elderly caring, etc. Yet the challenges residing in real-time contact feedback\u0000have hindered further applications in precise manipulation. This paper proposes\u0000an end-to-end network to estimate the 3D contact force of the soft robot, with\u0000the aim of enhancing its capabilities in interactive tasks. The presented\u0000method features directly utilizing monocular images fused with multidimensional\u0000actuation information as the network inputs. This approach simplifies the\u0000preprocessing of raw data compared to related studies that utilize 3D shape\u0000information for network inputs, consequently reducing configuration\u0000reconstruction errors. The unified feature representation module is devised to\u0000elevate low-dimensional features from the system's actuation signals to the\u0000same level as image features, facilitating smoother integration of multimodal\u0000information. The proposed method has been experimentally validated in the soft\u0000robot testbed, achieving satisfying accuracy in 3D force estimation (with a\u0000mean relative error of 0.84% compared to the best-reported result of 2.2% in\u0000the related works).","PeriodicalId":501031,"journal":{"name":"arXiv - CS - Robotics","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142222095","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

LED: Light Enhanced Depth Estimation at Night 发光二极管夜间光增强深度估计

arXiv - CS - Robotics Pub Date : 2024-09-12 DOI: arxiv-2409.08031

Simon de Moreau, Yasser Almehio, Andrei Bursuc, Hafid El-Idrissi, Bogdan Stanciulescu, Fabien Moutarde

引用次数: 0