2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)最新文献_第5页

Uniform Global Exponential Stabilizing Passivity-Based Tracking Controller Applied to Planar Biped Robots 基于全局指数稳定的平面双足机器人无源跟踪控制器

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9981206

Pierluigi Arpenti, A. Donaire, Fabio Ruggiero, V. Lippiello

引用次数: 0

Simultaneous Depth Estimation and Localization for Cell Manipulation Based on Deep Learning 基于深度学习的细胞操作同步深度估计和定位

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9982228

Zengshuo Wang, Huiying Gong, Ke-yong Li, Bin Yang, Yue Du, Yaowei Liu, Xin Zhao, Mingzhu Sun

{"title":"Simultaneous Depth Estimation and Localization for Cell Manipulation Based on Deep Learning","authors":"Zengshuo Wang, Huiying Gong, Ke-yong Li, Bin Yang, Yue Du, Yaowei Liu, Xin Zhao, Mingzhu Sun","doi":"10.1109/IROS47612.2022.9982228","DOIUrl":"https://doi.org/10.1109/IROS47612.2022.9982228","url":null,"abstract":"Visual localization, which is a key technology to realize the automation of cell manipulation, has been widely studied. Since the depth of field of the microscope is narrow, the planar localization and depth estimation are usually coupled together. At present, most methods adopt the serial working mode of focusing first and then planar localization, but they usually do not have good real-time performance and stability. In this paper, a simultaneous depth estimation and localization network was developed for cell manipulation. The network takes a focused image and a defocus-offset image as inputs, and outputs the defocus in the depth direction and the offset in the plane at the same time after going through defocus-offset information extraction, defocus classification mapping and offset regression mapping. To train and test our network, we also create two datasets: An Adherent Cell dataset and an Injection Micropipette dataset. The experimental results demonstrated that the proposed method achieves the detection of all test samples with a frame rate of more than 40Hz, and the maximum errors of depth estimation and localization are $boldsymbol{2.44mu m}$ and $boldsymbol{0.49mu m}$, respectively. The proposed method has good stability, which is mainly reflected in its strong generalization ability and anti-noise ability.","PeriodicalId":431373,"journal":{"name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121559728","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

An Event-triggered Visual Servoing Predictive Control Strategy for the Surveillance of Contour-based Areas using Multirotor Aerial Vehicles 多旋翼飞行器基于等高线区域监视的事件触发视觉伺服预测控制策略

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9981176

Sotirios N. Aspragkathos, Mario Sinani, G. Karras, Fotis Panetsos, K. Kyriakopoulos

{"title":"An Event-triggered Visual Servoing Predictive Control Strategy for the Surveillance of Contour-based Areas using Multirotor Aerial Vehicles","authors":"Sotirios N. Aspragkathos, Mario Sinani, G. Karras, Fotis Panetsos, K. Kyriakopoulos","doi":"10.1109/IROS47612.2022.9981176","DOIUrl":"https://doi.org/10.1109/IROS47612.2022.9981176","url":null,"abstract":"In this paper, an Event-triggered Image-based Visual Servoing Nonlinear Model Predictive Controller (ET-IBVS-NMPC) for multirotor aerial vehicles is presented. The proposed scheme is developed for the autonomous surveillance of contour-based areas with different characteristics (e.g. forest paths, coastlines, road pavements). For this purpose, an appropriately trained Deep Neural Network (DNN) is employed for the accurate detection of the contours. In an effort to reduce the remarkably large computational cost required by an IBVS-NMPC algorithm, a triggering condition is designed to define when the Optimal Control Problem (OCP) should be resolved and new control inputs will be calculated. Between two successive triggering instants, the control input trajectory is applied to the robot in an open-loop fashion, which means that no control input computations are required. As a result, the system's computing effort and energy consumption are lowered, while its autonomy and flight duration are increased. The visibility and input constraints, as well as the external disturbances, are all taken into account throughout the control design. The efficacy of the proposed strategy is demonstrated through a series of real-time experiments using a quadrotor and an octorotor both equipped with a monocular downward looking camera.","PeriodicalId":431373,"journal":{"name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127670153","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

Gaussian Variational Inference with Covariance Constraints Applied to Range-only Localization 基于协方差约束的高斯变分推理在距离定位中的应用

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9981520

Abhishek Goudar, Wenda Zhao, T. Barfoot, Angela P. Schoellig

引用次数: 2

ProTAMP: Probabilistic Task and Motion Planning Considering Human Action for Harmonious Collaboration 考虑人类行为的和谐协作的概率任务和运动规划

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9982074

Shun Mochizuki, Yosuke Kawasaki, Masaki Takahashi

{"title":"ProTAMP: Probabilistic Task and Motion Planning Considering Human Action for Harmonious Collaboration","authors":"Shun Mochizuki, Yosuke Kawasaki, Masaki Takahashi","doi":"10.1109/IROS47612.2022.9982074","DOIUrl":"https://doi.org/10.1109/IROS47612.2022.9982074","url":null,"abstract":"For the proper functioning of mobile manipulator-type autonomous robot performing complicated tasks in a human-robot coexistence environment, tasks and motions must be planned simultaneously. In such environments, a human and robot should collaborate with each other. Therefore, the robot must act in accordance with the human and avoid useless actions duplicated with those of humans. However, any action undertaken by a human has uncertainty, and thus, predicting them correctly is challenging. This study proposed probabilistic task and motion planning considering both deterministic and probabilistic environment changes caused by robot and human actions temporarily and spatially, respectively. First, the environmental changes were modeled, where the robot is capable of recognizing the possibility of environmental changes. Second, in task planning, the probabilities of each environmental change owing to human actions was minimized. Finally, in motion planning, a movement path connecting each task in a planned order was planned, thereby enabling the robot to perform actions not duplicated with those by a human. Furthermore, the plans generated were compared without considering possibility of human actions and the effectiveness of the proposed method was verified. Consequently, the proposed method was confirmed to reduce the time required for finishing the tasks.","PeriodicalId":431373,"journal":{"name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"2017 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125737867","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

Slip Anticipation for Grasping Deformable Objects Using a Soft Force Sensor 基于软力传感器的可变形物体抓取滑移预估

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9981174

E. Judd, B. Aksoy, K. M. Digumarti, H. Shea, D. Floreano

{"title":"Slip Anticipation for Grasping Deformable Objects Using a Soft Force Sensor","authors":"E. Judd, B. Aksoy, K. M. Digumarti, H. Shea, D. Floreano","doi":"10.1109/IROS47612.2022.9981174","DOIUrl":"https://doi.org/10.1109/IROS47612.2022.9981174","url":null,"abstract":"Robots using classical control have revolutionised assembly lines where the environment and manipulated objects are restricted and predictable. However, they have proven less effective when the manipulated objects are deformable due to their complex and unpredictable behaviour. The use of tactile sensors and continuous monitoring of tactile feedback is there-fore particularly important for pick-and-place tasks using these materials. This is in part due to the need to use multiple points of contact for the manipulation of deformable objects which can result in slippage with inadequate coordination between manipulators. In this paper, continuous monitoring of tactile feedback, using a liquid metal soft force sensor, for grasping deformable objects is presented. The trained data-driven model distinguishes between successful grasps, slippage and failure during a manipulation task for multiple deformable objects. Slippage could be anticipated before failure occurred using data acquired over a 30 ms period with a greater than 95% accuracy using a random forest classifier. The results were achieved using a single sensor that can be mounted on the fingertips of existing grippers and contributes to the development of an automated pick-and-place process for deformable objects.","PeriodicalId":431373,"journal":{"name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"240 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125763471","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

Multi-Object Grasping - Efficient Robotic Picking and Transferring Policy for Batch Picking 多目标抓取-高效机器人拾取与批量拾取转移策略

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9981799

Adheesh Shenoy, Tianze Chen, Yu Sun

{"title":"Multi-Object Grasping - Efficient Robotic Picking and Transferring Policy for Batch Picking","authors":"Adheesh Shenoy, Tianze Chen, Yu Sun","doi":"10.1109/IROS47612.2022.9981799","DOIUrl":"https://doi.org/10.1109/IROS47612.2022.9981799","url":null,"abstract":"In a typical fulfillment center, the order fulfilling process is managed by a warehouse management system (WMS). For efficiency, WMS usually applies batch picking, also called multi-order picking, to collect the same items for multiple orders. Suppose an item appears in multiple orders, instead of repeatedly revisiting the exact picking location multiple times, a picker will be instructed to pick up multiple same items at once and bring them to a sorting station, also called a re-bin station. It is at the re-bin station, where the workers sort the picked items into separate orders. We have seen many robotic technologies being developed for sorting. However, we have not seen any feasible robotic technology for batch picking. Transferring multiple objects between bins is a common task. In robotics, a standard approach is to transfer a single object at a time. However, grasping multiple objects and transferring them at once is more efficient. This paper presents a set of novel strategies for efficiently grasping and transferring multiple objects. The grasping strategies enable a robotic hand to grasp multiple objects by identifying an optimal ready hand configuration (pre-grasp), calculating a flexion synergy based on the desired quantity of objects to be grasped, and utilizing a deep learning model to signal the completion of a grasp. The transferring strategies demonstrate an approach that models the problem as a Markov decision process (MDP) and defines specific grasping actions to efficiently transfer objects when the required quantity is larger than the capability of a single grasp. Using the MDP model, the approach can generate an optimal pick-transfer policy that minimizes the number of transfers. The complete proposed approach has been evaluated in both a simulation environment and on a real robotic system. The proposed approach reduces the number of transfers by 59% and the number of lifts by 58% compared to an optimal single object pick-transfer solution.","PeriodicalId":431373,"journal":{"name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115774963","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

Robot Dance Generation with Music Based Trajectory Optimization 基于音乐轨迹优化的机器人舞蹈生成

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9981462

Melya Boukheddimi, D. Harnack, Shivesh Kumar, Rohit Kumar, S. Vyas, Octavio Arriaga, F. Kirchner

引用次数: 3

Hierarchical Learning and Control for In-Hand Micromanipulation Using Multiple Laser-Driven Micro-Tools 基于多激光驱动微工具的手持式微操作层次学习与控制

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9982033

Yongyi Jia, Yu Chen, Hao Liu, Xiu Li, Xiang Li

{"title":"Hierarchical Learning and Control for In-Hand Micromanipulation Using Multiple Laser-Driven Micro-Tools","authors":"Yongyi Jia, Yu Chen, Hao Liu, Xiu Li, Xiang Li","doi":"10.1109/IROS47612.2022.9982033","DOIUrl":"https://doi.org/10.1109/IROS47612.2022.9982033","url":null,"abstract":"Laser-driven micro-tools are formulated by treating highly-focused laser beams as actuators, to control the tool's motion to contact then manipulate a micro object, which allows it to manipulate opaque micro objects, or large cells without causing photodamage. However, most existing laser-driven tools are limited to relatively simple tasks, such as moving and caging, and cannot carry out in-hand dexterous tasks. This is mainly because in-hand manipulation involves continuously coordinating multiple laser beams, micro-tools, and the object itself, which has high degrees of freedom (DoF) and poses up challenge for planner and controller design. This paper presents a new hierarchical formulation for the grasping and manipulation of micro objects using multiple laser-driven micro-tools. In hardware, multiple laser-driven tools are assembled to act as a robotic hand to carry out in-hand tasks (e.g., rotating); in software, a hierarchical scheme is developed to shrunken the action space and coordinate the motion of multiple tools, subject to both the parametric uncertainty in the tool and the unknown dynamic model of the object. Such a formulation provides potential for achieving robotic in-hand manipulation at a micro scale. The performance of the proposed system is validated in simulation studies under different scenarios.","PeriodicalId":431373,"journal":{"name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132132635","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

Probabilistic Planning for AUV Data Harvesting from Smart Underwater Sensor Networks 基于智能水下传感器网络的AUV数据采集的概率规划

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9981460

Matthew Budd, G. Salavasidis, Izzat Karnarudzaman, C. Harris, A. Phillips, Paul Duckworth, N. Hawes, Bruno Lacerda

{"title":"Probabilistic Planning for AUV Data Harvesting from Smart Underwater Sensor Networks","authors":"Matthew Budd, G. Salavasidis, Izzat Karnarudzaman, C. Harris, A. Phillips, Paul Duckworth, N. Hawes, Bruno Lacerda","doi":"10.1109/IROS47612.2022.9981460","DOIUrl":"https://doi.org/10.1109/IROS47612.2022.9981460","url":null,"abstract":"Harvesting valuable ocean data, ranging from climate and marine life analysis to industrial equipment monitoring, is an extremely challenging real-world problem. Sparse underwater sensor networks are a promising approach to scale to larger and deeper environments, but these have difficulty offloading their data without external assistance. Traditionally, offloading data has been achieved by costly, fixed communication infrastructure. In this paper, we propose a planning under uncertainty method that enables an autonomous underwater vehicle (AUV) to adaptively collect data from smart sensor networks in underwater environments. Our novel solution exploits the ability of sensor nodes to provide the AUV with time-of-flight acoustic localisation, and is able to prioritise nodes with the most valuable data. In both simulated experiments and a real-world field trial, we demonstrate that our method outperforms the type of hand-designed behaviours that has previously been used in the context of underwater data harvesting.","PeriodicalId":431373,"journal":{"name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132302998","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: 1