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

GoferBot: A Visual Guided Human-Robot Collaborative Assembly System GoferBot:一个视觉引导的人机协作装配系统

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9981122

Zheyu Zhuang, Yizhak Ben-Shabat, Jiahao Zhang, Stephen Gould, R. Mahony

{"title":"GoferBot: A Visual Guided Human-Robot Collaborative Assembly System","authors":"Zheyu Zhuang, Yizhak Ben-Shabat, Jiahao Zhang, Stephen Gould, R. Mahony","doi":"10.1109/IROS47612.2022.9981122","DOIUrl":"https://doi.org/10.1109/IROS47612.2022.9981122","url":null,"abstract":"The current transformation towards smart manufacturing has led to a growing demand for human-robot collaboration (HRC) in the manufacturing process. Perceiving and understanding the human co-worker's behaviour introduces challenges for collaborative robots to efficiently and effectively perform tasks in unstructured and dynamic environments. Integrating recent data-driven machine vision capabilities into HRC systems is a logical next step in addressing these challenges. However, in these cases, off-the-shelf components struggle due to generalisation limitations. Real-world evaluation is required in order to fully appreciate the maturity and robustness of these approaches. Furthermore, understanding the pure-vision aspects is a crucial first step before combining multiple modalities in order to understand the limitations. In this paper, we propose GoferBot, a novel vision-based semantic HRC system for a real-world assembly task. It is composed of a visual servoing module that reaches and grasps assembly parts in an unstructured multi-instance and dynamic environment, an action recognition module that performs human action prediction for implicit communication, and a visual handover module that uses the perceptual understanding of human behaviour to produce an intuitive and efficient collaborative assembly experience. GoferBot is a novel assembly system that seamlessly integrates all sub-modules by utilising implicit semantic information purely from visual perception.","PeriodicalId":431373,"journal":{"name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"72 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":"115386646","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

Safety Guided Policy Optimization 安全导向的政策优化

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9981030

Dohyeong Kim, Yunho Kim, Kyungjae Lee, Songhwai Oh

{"title":"Safety Guided Policy Optimization","authors":"Dohyeong Kim, Yunho Kim, Kyungjae Lee, Songhwai Oh","doi":"10.1109/IROS47612.2022.9981030","DOIUrl":"https://doi.org/10.1109/IROS47612.2022.9981030","url":null,"abstract":"In reinforcement learning (RL), exploration is essential to achieve a globally optimal policy but unconstrained exploration can cause damages to robots and nearby people. To handle this safety issue in exploration, safe RL has been proposed to keep the agent under the specified safety constraints while maximizing cumulative rewards. This paper introduces a new safe RL method which can be applied to robots to operate under the safety constraints while learning. The key component of the proposed method is the safeguard module. The safeguard predicts the constraints in the near future and corrects actions such that the predicted constraints are not violated. Since actions are safely modified by the safeguard during exploration and policies are trained to imitate the corrected actions, the agent can safely explore. Additionally, the safeguard is sample efficient as it does not require long horizontal trajectories for training, so constraints can be satisfied within short time steps. The proposed method is extensively evaluated in simulation and experiments using a real robot. The results show that the proposed method achieves the best performance while satisfying safety constraints with minimal interaction with environments in all experiments.","PeriodicalId":431373,"journal":{"name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"3 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":"115723838","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

E2Pose: Fully Convolutional Networks for End-to-End Multi-Person Pose Estimation E2Pose:端到端多人姿态估计的全卷积网络

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9981322

Masakazu Tobeta, Y. Sawada, Ze Zheng, Sawa Takamuku, N. Natori

引用次数: 2

MS-cubic: A Modularized Manufacturing System with scalability, portability and parallelism Modular design suitable for drilling, welding and picking and feasibility verification through drilling experiment MS-cubic:具有可扩展性、可移植性和并行性的模块化制造系统。模块化设计适用于钻孔、焊接和拣选，并通过钻孔实验验证可行性

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9981791

Takehito Yoshida, Amane Toriyama, S. Warisawa, R. Fukui

{"title":"MS-cubic: A Modularized Manufacturing System with scalability, portability and parallelism Modular design suitable for drilling, welding and picking and feasibility verification through drilling experiment","authors":"Takehito Yoshida, Amane Toriyama, S. Warisawa, R. Fukui","doi":"10.1109/IROS47612.2022.9981791","DOIUrl":"https://doi.org/10.1109/IROS47612.2022.9981791","url":null,"abstract":"The existing manufacturing systems based on processes involving the transportation of workpiece are unsuitable for large products such as air mobility systems. This study proposes a novel ultra-complex manufacturing system called the “Modularized-Structure and Multiple-Points Simultaneous Machining System (MS-cubic)” based on the concept of intelligent space, which simultaneously performs multiple types of machining processes without moving a workpiece. The system can simultaneously process multiple points and flexibly change its workspace by modularizing its structure. This paper presents a discussion on the requirements and constraints to generate a feasible design of the rail module and the machining unit, which are two main elements of MS-cubic. The performance of the prototype MS-cubic is evaluated, and its stiffness is observed to be sufficient to perform drilling. Furthermore, the modularized design of system enables the fluid and electric power supply for the machining process.","PeriodicalId":431373,"journal":{"name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"143 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":"116907184","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

Task Decoupling in Preference-based Reinforcement Learning for Personalized Human-Robot Interaction 个性化人机交互中基于偏好强化学习的任务解耦

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9981076

Mingjiang Liu, Chunlin Chen

{"title":"Task Decoupling in Preference-based Reinforcement Learning for Personalized Human-Robot Interaction","authors":"Mingjiang Liu, Chunlin Chen","doi":"10.1109/IROS47612.2022.9981076","DOIUrl":"https://doi.org/10.1109/IROS47612.2022.9981076","url":null,"abstract":"Intelligent robots designed to interact with hu-mans in the real world need to adapt to the preferences of different individuals. Preference-based reinforcement learning (RL) has shown great potential for teaching robots to learn personalized behaviors from interacting with humans with-out a meticulous, hand-crafted reward function, replaced by learning reward based on a human's preferences between two robot trajectories. However, poor feedback efficiency and poor exploration in the state and reward spaces make current preference-based RL algorithms perform poorly in complex interactive tasks. To improve the performance of preference-based RL, we incorporate prior knowledge of the task into preference-based RL. Specifically, we decouple the task from preference in human-robot interaction. We utilize a sketchy task reward derived from task priori to instruct robots to conduct more effective task exploration. Then a learned reward from preference-based RL is used to optimize the robot's policy to align with human preferences. In addition, these two parts are combined organically via reward shaping. The experimental results show that our method is a practical and effective solution for personalized human-robot interaction. Code is available at https://github.com/Wenminggong/PbRL_for_PHRI.","PeriodicalId":431373,"journal":{"name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"63 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121009682","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

Development of a cable-driven Growing Sling to assist patient transfer 缆索驱动生长吊带的发展，以协助病人转移

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9981770

Myung-Il Lee, Yong-Ky Moon, Jeongryul Kim, Seungjun Lee, Keri Kim, Hyunki In

{"title":"Development of a cable-driven Growing Sling to assist patient transfer","authors":"Myung-Il Lee, Yong-Ky Moon, Jeongryul Kim, Seungjun Lee, Keri Kim, Hyunki In","doi":"10.1109/IROS47612.2022.9981770","DOIUrl":"https://doi.org/10.1109/IROS47612.2022.9981770","url":null,"abstract":"As the aging of society continues to accelerate, the number of elderly patients is increasing, as is the demand for manpower to care for them. In particular, there is an urgent need for bedridden patient care. However, limitations in the supply of human resources have caused an increase in the burden for care. In particular, nursing personnel often experience inconvenience and difficulties owing to the great deal of effort required to transfer a patient from bed to wheelchair, or vice versa. The most difficult process during the patient transfer is inserting the sling under the patient. Aiming to solve this problem, a mechanical Growing Sling was devised. The proposed sling adapts a growing mechanism comprising a low-friction fabric and steel shafts, and the sling is inserted under the patient by towing the steel shafts with cables connected to a motor. For the comfort and safety of the sling insertion, the required towing force was analyzed to find the minimum diameter of the shaft. The results from experimental evaluations using the proposed sling verified that it can be inserted under the patient without moving the patient, and with an acceptable level of pressure being applied to the patient.","PeriodicalId":431373,"journal":{"name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"72 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":"127133904","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

Model Learning and Predictive Control for Autonomous Obstacle Reduction via Bulldozing 推土机自动减障的模型学习与预测控制

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9981911

W. J. Wagner, K. Driggs-Campbell, A. Soylemezoglu

{"title":"Model Learning and Predictive Control for Autonomous Obstacle Reduction via Bulldozing","authors":"W. J. Wagner, K. Driggs-Campbell, A. Soylemezoglu","doi":"10.1109/IROS47612.2022.9981911","DOIUrl":"https://doi.org/10.1109/IROS47612.2022.9981911","url":null,"abstract":"We investigate how employing model learning methods in concert with model predictive control (MPC) can be used to automate obstacle reduction to mitigate risks to Combat Engineers operating construction equipment in an active battlefield. We focus on the task of earthen berm removal using a bladed vehicle. We introduce a novel data-driven formulation for earthmoving dynamics that enables prediction of the vehicle and detailed terrain state over a one second horizon. In a simulation environment, we first record demonstrations from a human operator and then train two different earthmoving models to produce predictions of the high-dimensional state using under six minutes of data. Optimization over the learned model is performed to select an action sequence, constrained to a 2D space of template action trajectories. Simple recovery controllers are implemented to improve controller performance when the model predictions degrade. This system yields near human-level performance on a berm removal task, indicating that model learning and predictive control is a promising data-efficient approach to autonomous earthmoving.","PeriodicalId":431373,"journal":{"name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"1 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":"127182641","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

Decay-Based Error Correction in Collective Robotic Construction 基于衰减的集体机器人构造误差校正

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9981721

Jiahe Chen, Kirstin H. Petersen

{"title":"Decay-Based Error Correction in Collective Robotic Construction","authors":"Jiahe Chen, Kirstin H. Petersen","doi":"10.1109/IROS47612.2022.9981721","DOIUrl":"https://doi.org/10.1109/IROS47612.2022.9981721","url":null,"abstract":"Multi-robot systems have been shown to build large-scale, user-specified structures using distributed, environmentally-mediated coordination in simulation. Little attention, however, has been devoted to error propagation and mitigation. In this paper, we introduce a detailed simulation of TERMES, a prototypical construction system, in which robots have realistic error profiles. We use this simulator and 32 randomly generated 250-brick blueprints to show that action errors can have significant long-term effects. We study the spatio-temporal error distribution and introduce and characterize the efficacy of a simple decay-based error correction mechanism. Although inefficient, this type of error correction is promising because it can be performed by robots with the same limited sensory capabilities as those who place bricks. To limit the impact on the construction rate, we also examine decay mechanisms informed by spatial and temporal error distributions. The incorporation of decay in our building process increases the probability of successful completion by ~ 4, at the expense of ~1/4 decrease in construction rate.","PeriodicalId":431373,"journal":{"name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"8 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":"127449404","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

Fast Scan Context Matching for Omnidirectional 3D Scan 全向三维扫描快速扫描上下文匹配

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9981143

Hikaru Kihara, M. Kumon, K. Nakatsuma, T. Furukawa

引用次数: 0

Monocular Event Visual Inertial Odometry based on Event-corner using Sliding Windows Graph-based Optimization 基于滑动窗口图优化的单目事件视觉惯性里程计

2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Pub Date : 2022-10-23 DOI: 10.1109/IROS47612.2022.9981970

W. Guan, P. Lu

{"title":"Monocular Event Visual Inertial Odometry based on Event-corner using Sliding Windows Graph-based Optimization","authors":"W. Guan, P. Lu","doi":"10.1109/IROS47612.2022.9981970","DOIUrl":"https://doi.org/10.1109/IROS47612.2022.9981970","url":null,"abstract":"Event cameras are biologically-inspired vision sensors that capture pixel-level illumination changes instead of the intensity image at a fixed frame rate. They offer many advantages over the standard cameras, such as high dynamic range, high temporal resolution (low latency), no motion blur, etc. Therefore, developing state estimation algorithms based on event cameras offers exciting opportunities for autonomous systems and robots. In this paper, we propose monocular visual-inertial odometry for event cameras based on event-corner feature detection and matching with well-designed feature management. More specifically, two different kinds of event representations based on time surface are designed to realize event-corner feature tracking (for front-end incremental estimation) and matching (for loop closure detection). Furthermore, the proposed event representations are used to set mask for detecting the event-corner feature based on the raw event-stream, which ensures the uniformly distributed and spatial consistency characteristic of the event-corner feature. Finally, a tightly coupled, graph-based optimization framework is designed to obtain high-accurate state estimation through fusing pre-integrated IMU measurements and event-corner observations. We validate quantitatively the performance of our system on different resolution event cameras: DAVIS240C (240*180, public dataset, achieve state-of-the-art), DAVIS346 (346*240, real-test), DVXplorer (640*480 real-test). Furthermore, we demonstrate qualitatively the accuracy, robustness, loop closure, and re-localization performance of our framework on different large-scale datasets, and an autonomous quadrotor flight using our Event Visual-inertial Odometry (EVIO) framework. Videos of all the evaluations are presented on the project website.","PeriodicalId":431373,"journal":{"name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","volume":"28 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":"125021092","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: 6