2022 International Conference on Robotics and Automation (ICRA)最新文献_第7页

Parametric Path Optimization for Wheeled Robots Navigation 轮式机器人导航参数路径优化

2022 International Conference on Robotics and Automation (ICRA) Pub Date : 2022-05-23 DOI: 10.1109/icra46639.2022.9812167

Zhiqiang Jian, Songyi Zhang, Jiahui Zhang, Shi-tao Chen, N. Zheng

引用次数: 1

The Second Generation (G2) Fingertip Sensor for Near-Distance Ranging and Material Sensing in Robotic Grasping* 第二代(G2)指尖传感器在机器人抓取中的近距离测距和材料传感*

2022 International Conference on Robotics and Automation (ICRA) Pub Date : 2022-05-23 DOI: 10.1109/icra46639.2022.9811902

Cheng Fang, Di Wang, Dezhen Song, Jun Zou

{"title":"The Second Generation (G2) Fingertip Sensor for Near-Distance Ranging and Material Sensing in Robotic Grasping*","authors":"Cheng Fang, Di Wang, Dezhen Song, Jun Zou","doi":"10.1109/icra46639.2022.9811902","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811902","url":null,"abstract":"To continuously improve robotic grasping, we are interested in developing a contactless fingertip-mounted sensor for near-distance ranging and material sensing. Previously, we demonstrated a dual-modal and dual sensing mechanisms (DMDSM) pretouch sensor prototype based on pulse-echo ultrasound and optoacoustics. However, the complex system, the bulky and expensive pulser-receiver, and the omni-directionally sensitive microphone block the sensor from practical applications in real robotic fingers. To address these issues, we report the second generation (G2) DMDSM sensor without the pulser-receiver and microphone, which is made possible by redesigning the ultrasound transmitter and receiver to gain much wider acoustic bandwidth. To verify our design, a prototype of the G2 DMDSM sensor has been fabricated and tested. The testing results show that the G2 DMDSM sensor can achieve better ranging and similar material/structure sensing performance, but with much-simplified configuration and operation. The primary results indicate that the G2 DMDSM sensor could provide a promising solution for fingertip pretouch sensing in robotic grasping.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"215 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128614598","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

Efficient and Robust Training of Dense Object Nets for Multi-Object Robot Manipulation 面向多目标机器人操作的密集目标网络的高效鲁棒训练

2022 International Conference on Robotics and Automation (ICRA) Pub Date : 2022-05-23 DOI: 10.48550/arXiv.2206.12145

David B. Adrian, A. Kupcsik, Markus Spies, H. Neumann

{"title":"Efficient and Robust Training of Dense Object Nets for Multi-Object Robot Manipulation","authors":"David B. Adrian, A. Kupcsik, Markus Spies, H. Neumann","doi":"10.48550/arXiv.2206.12145","DOIUrl":"https://doi.org/10.48550/arXiv.2206.12145","url":null,"abstract":"We propose a framework for robust and efficient training of Dense Object Nets (DON) [1] with a focus on industrial multi-object robot manipulation scenarios. DON is a popular approach to obtain dense, view-invariant object descriptors, which can be used for a multitude of downstream tasks in robot manipulation, such as, pose estimation, state representation for control, etc. However, the original work [1] focused training on singulated objects, with limited results on instance-specific, multi-object applications. Additionally, a complex data collection pipeline, including 3D reconstruction and mask annotation of each object, is required for training. In this paper, we further improve the efficacy of DON with a simplified data collection and training regime, that consistently yields higher precision and enables robust tracking of keypoints with less data requirements. In particular, we focus on training with multi-object data instead of singulated objects, combined with a well-chosen augmentation scheme. We additionally propose an alternative loss formulation to the original pixel wise formulation that offers better results and is less sensitive to hyperparameters. Finally, we demonstrate the robustness and accuracy of our proposed framework on a real-world robotic grasping task.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"230 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128619406","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

Safe endoscope holding in minimally invasive surgery: zero stiffness and adaptive weight compensation 微创手术中安全的内窥镜保持:零刚度和适应性重量补偿

2022 International Conference on Robotics and Automation (ICRA) Pub Date : 2022-05-23 DOI: 10.1109/icra46639.2022.9811359

Jesus Mago, F. Louveau, M. Vitrani, G. Morel

{"title":"Safe endoscope holding in minimally invasive surgery: zero stiffness and adaptive weight compensation","authors":"Jesus Mago, F. Louveau, M. Vitrani, G. Morel","doi":"10.1109/icra46639.2022.9811359","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811359","url":null,"abstract":"One of the major functions brought by robots in Minimally Invasive Surgery is endoscope holding. This consists, for the user, in placing the camera at a desired location which the robot will maintain still once he/she releases it. This behavior is usually achieved with rigid position servoing, leading to possibly high forces generated and safety issues. Model-based weight compensation is an alternative solution. However, endoscopic cameras' weight is difficult to model as their gravity parameters can change during the same surgery. In this paper, an algorithm is presented as an option to cope with this variability in the gravity model without using rigid position servoing. The surgeon first positions the camera in a comanipulation mode (gravity compensation). When he/she releases the camera, if the gravity model is not accurate, the endoscope presents a drift. In this case, a controller brings the endoscope back to its release position by combining low gain position control and model adaptation. Once stabilized, the system is switched back to a zero-stiffness mode. Two in-vitro experiments were performed in which a user manipulates an endoscope whose configuration of mass is changed. In one case, the mass in the gravity model was set to half of the actual one. In the second case, a variable weight was attached to the endoscope. The algorithm successfully updated the model for each experiment reducing position errors by 95% and 57%, respectively.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129605406","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 Data-Driven Multiple Model Framework for Intention Estimation 一种数据驱动的多模型意图估计框架

2022 International Conference on Robotics and Automation (ICRA) Pub Date : 2022-05-23 DOI: 10.1109/icra46639.2022.9812432

Yongming Qin, M. Kumon, T. Furukawa

{"title":"A Data-Driven Multiple Model Framework for Intention Estimation","authors":"Yongming Qin, M. Kumon, T. Furukawa","doi":"10.1109/icra46639.2022.9812432","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812432","url":null,"abstract":"This paper presents a data-driven multiple model framework for estimating the intention of a target from observations. Multiple model (MM) state estimation methods have been extensively used for intention estimation by mapping one intention to one dynamic model assuming one-to-one relations. However, intentions are subjective to humans and it is difficult to establish the one-to-one relations explicitly. The proposed framework infers the multiple-to-multiple relations between intentions and models directly from observations that are labeled with intentions. For intention estimation, both the relations and model probabilities of an Interacting Multiple Model (IMM) state estimation approach are integrated into a recursive Bayesian framework. Taking advantage of the inferred multiple-to-multiple relations, the framework incorpo-rates more accurate relations and avoids following the strict one-to-one relations. Numerical and real experiments were performed to investigate the framework through the intention estimation of a maneuvered quadrotor. Results show higher estimation accuracy and superior flexibility in designing mod-els over the conventional approach that assumes one-to-one relations.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"473 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127550925","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

WeakLabel3D-Net: A Complete Framework for Real-Scene LiDAR Point Clouds Weakly Supervised Multi-Tasks Understanding WeakLabel3D-Net:弱监督多任务理解的真实场景激光雷达点云完整框架

2022 International Conference on Robotics and Automation (ICRA) Pub Date : 2022-05-23 DOI: 10.1109/icra46639.2022.9811959

Kangcheng Liu, Yuzhi Zhao, Z. Gao, Ben M. Chen

{"title":"WeakLabel3D-Net: A Complete Framework for Real-Scene LiDAR Point Clouds Weakly Supervised Multi-Tasks Understanding","authors":"Kangcheng Liu, Yuzhi Zhao, Z. Gao, Ben M. Chen","doi":"10.1109/icra46639.2022.9811959","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811959","url":null,"abstract":"Existing state-of-the-art 3D point clouds understanding methods only perform well in a fully supervised manner. To the best of our knowledge, there exists no unified framework which simultaneously solves the downstream high-level understanding tasks, especially when labels are extremely limited. This work presents a general and simple framework to tackle point clouds understanding when labels are limited. We propose a novel unsupervised region expansion based clustering method for generating clusters. More importantly, we innovatively propose to learn to merge the over-divided clusters based on the local low-level geometric property similarities and the learned high-level feature similarities supervised by weak labels. Hence, the true weak labels guide pseudo labels merging taking both geometric and semantic feature correlations into consideration. Finally, the self-supervised data augmentation optimization module is proposed to guide the propagation of labels among semantically similar points within a scene. Experimental Results demonstrate that our framework has the best performance among the three most important weakly supervised point clouds understanding tasks including semantic segmentation, instance segmentation, and object detection even when limited points are labeled.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129942159","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: 21

A Detumbling Strategy for an Orbital Manipulator in the Post-Grasp Phase 轨道机械臂后抓取阶段的跌落策略

2022 International Conference on Robotics and Automation (ICRA) Pub Date : 2022-05-23 DOI: 10.1109/icra46639.2022.9812067

R. Vijayan, M. Stefano, C. Ott

{"title":"A Detumbling Strategy for an Orbital Manipulator in the Post-Grasp Phase","authors":"R. Vijayan, M. Stefano, C. Ott","doi":"10.1109/icra46639.2022.9812067","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812067","url":null,"abstract":"In this paper, we propose a detumbling strategy that stabilizes the motion of a tumbling client satellite using an orbital servicing manipulator, which is the goal of the post-grasp phase. One of the critical aspects in this phase is ensuring that excessive contact forces are not generated at the grasp interface. In addition, space mission requirements might demand a nominal manipulator configuration that is suitable for further manipulation/servicing activities. The proposed strategy allows the detumbling of the client motion while ensuring that the contact forces developed at the grasp interface do not violate a safety threshold. Further, it allows the reconfiguration of the manipulator arm by exploiting the full actuation capability of the manipulator-equipped servicing spacecraft. The controller guarantees joint task convergence in the nullspace of the manipulator's end-effector, and is also valid for kinematically singular configurations of the manipulator. It is further augmented using a quadratic programming based approach to optimally constrain the contact forces. Finally, simulation results for a post-grasp detumbling scenario are shown to validate the effectiveness of the proposed method.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128946543","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

Strawberry picking point localization ripeness and weight estimation 草莓采摘点定位、成熟度及重量估算

2022 International Conference on Robotics and Automation (ICRA) Pub Date : 2022-05-23 DOI: 10.1109/icra46639.2022.9812303

Alessandra Tafuro, Adeayo Adewumi, Soran Parsa, Ghalamzan E. Amir, Bappaditya Debnath

{"title":"Strawberry picking point localization ripeness and weight estimation","authors":"Alessandra Tafuro, Adeayo Adewumi, Soran Parsa, Ghalamzan E. Amir, Bappaditya Debnath","doi":"10.1109/icra46639.2022.9812303","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812303","url":null,"abstract":"Labour shortage, difficulties in labour management, the digitalization of fruit production pipeline to reduce the fruit production costs have made robotic systems for selective harvesting of strawberries an important industry and academic research. One of the important components of such technologies yet to be developed is fruit picking perception. For picking strawberries, a robot needs to infer the location of picking points from the images of strawberries. Moreover, the size and weight of strawberries to be picked can help the robot to place the picked strawberries in proper punnets directly to be delivered to customers in supermarkets. This can save significant time and packing costs in packhouses. Geometry-based approaches are the most common approach to determine the picking point but they suffer from inaccuracies due to noise, occlusion, and varying shape and orientation of the berries. In contrast, we present two novel datasets of strawberries annotated with picking points, key-points (such as the shoulder points, the contact point between the calyx and flesh, and the point on the flesh farthest from the calyx), and the weight and size of the berries. We performed experiments with Detectron-2, which is an extended version of Mask-RCNN with key-points detection capability. The results show that the key-points detection approach works well for picking and grasping point localization. The second dataset also presents the dimensions and weight of strawberries. Our novel baseline model for weight estimation outperforms many state-of-the-art deep networks. The datasets and annotations are available at https://github.com/imanlab/strawberry-pp-w-r-dataset.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"8 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125659253","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

Autonomous Ultrasound Scanning using Bayesian Optimization and Hybrid Force Control 基于贝叶斯优化和混合力控制的自主超声扫描

2022 International Conference on Robotics and Automation (ICRA) Pub Date : 2022-05-23 DOI: 10.1109/icra46639.2022.9812410

Raghavv Goel, Fnu Abhimanyu, Kirtan Patel, J. Galeotti, H. Choset

{"title":"Autonomous Ultrasound Scanning using Bayesian Optimization and Hybrid Force Control","authors":"Raghavv Goel, Fnu Abhimanyu, Kirtan Patel, J. Galeotti, H. Choset","doi":"10.1109/icra46639.2022.9812410","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9812410","url":null,"abstract":"Ultrasound scanning is an imaging technique that aids medical professionals in diagnostics and interventional procedures. However, a trained human-in-the-loop (HITL) with a radiologist is required to perform the scanning procedure. We seek to create a novel ultrasound system that can provide imaging in the absence of a trained radiologist, say for patients in the field who suffered injuries after a natural disaster. One challenge of automating ultrasound scanning involves finding the optimal area to scan and then performing the actual scan. This task requires simultaneously maintaining contact with the surface while moving along it to capture high quality images. In this work, we present an automated Robotic Ultrasound System (RUS) to tackle these challenges. Our approach introduces a Bayesian Optimization framework to guide the probe to multiple points on the unknown surface. Our proposed framework collects the ultrasound images as well as the pose information at every probed point to estimate regions with high vessel density (information map) and the surface contour. Based on the information map and the surface contour, an area of interest is selected for scanning. Furthermore, to scan the proposed region, a novel 6-axis hybrid force-position controller is presented to ensure acoustic coupling. Lastly, we provide experimental results on two different phantom models to corroborate our approach.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128907585","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: 8

Value learning from trajectory optimization and Sobolev descent: A step toward reinforcement learning with superlinear convergence properties 基于轨迹优化和Sobolev下降的价值学习:向具有超线性收敛特性的强化学习迈出的一步

2022 International Conference on Robotics and Automation (ICRA) Pub Date : 2022-05-23 DOI: 10.1109/icra46639.2022.9811993

Amit Parag, Sébastien Kleff, Léo Saci, N. Mansard, O. Stasse

{"title":"Value learning from trajectory optimization and Sobolev descent: A step toward reinforcement learning with superlinear convergence properties","authors":"Amit Parag, Sébastien Kleff, Léo Saci, N. Mansard, O. Stasse","doi":"10.1109/icra46639.2022.9811993","DOIUrl":"https://doi.org/10.1109/icra46639.2022.9811993","url":null,"abstract":"The recent successes in deep reinforcement learning largely rely on the capabilities of generating masses of data, which in turn implies the use of a simulator. In particular, current progress in multi body dynamic simulators are under-pinning the implementation of reinforcement learning for end-to-end control of robotic systems. Yet simulators are mostly considered as black boxes while we have the knowledge to make them produce a richer information. In this paper, we are proposing to use the derivatives of the simulator to help with the convergence of the learning. For that, we combine model-based trajectory optimization to produce informative trials using 1st- and 2nd-order simulation derivatives. These locally-optimal runs give fair estimates of the value function and its derivatives, that we use to accelerate the convergence of the critics using Sobolev learning. We empirically demonstrate that the algorithm leads to a faster and more accurate estimation of the value function. The resulting value estimate is used in model-predictive controller as a proxy for shortening the preview horizon. We believe that it is also a first step toward superlinear reinforcement learning algorithm using simulation derivatives, that we need for end-to-end legged locomotion.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130750432","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: 7