满足不同交互任务的人机共融系统设计

人与机器人共同协作的灵活生产模式已经成为工业成产的迫切需求, 因此, 近年来人机共融系统方面的研究受到了越来越多关注. 设计并实现了一种满足不同交互任务的人机共融系统, 人体动作的估计和机器人的交互控制是其中的关键技术. 首先, 提出了一种基于多相机和惯性测量单元信息融合的人体姿态解算方法, 通过构造优化问题, 融合多相机下的2D关节检测信息和所佩戴的惯性测量单元测量信息, 对人体运动学姿态进行优化估计, 改善了单一传感器下, 姿态信息不全面以及对噪声敏感的问题, 提升了姿态估计的准确度. 其次, 结合机器人的运动学特性和人机交互的特点, 设计了基于目标点跟踪和模型预测控制的机器人控制策略, 使得机器人能够通过调整控制参数, 适应动态的环境和不同的交互需求, 同时保证机器人和操作人员的安全. 最后, 进行了动作跟随、物品传递、主动避障等人机交互实验, 实验结果表明了所设计的机器人交互系统在人机共融环境下的有效性和可靠性.     

MFR (Multipurpose Field Robot) for installing construction materials

The objective of the study was to propose a MFR (Multipurpose Field Robot) in hazardous operation environments. This system combines a basic system composed of a multi-DOF (Degree Of Freedom) manipulator and a mobile platform with an additional module for construction, national defense and emergency-rescue. According to an additional module type combined with a basic system, it can be used in a various fields. In this study, we describe a prototype of construction robot which helps a human operator handle easily construction materials in case of using the cooperation system on construction site. This study introduces an additional module for construction and a robot control algorithm for a HRC (Human-Robot Cooperation). In addition, it proposes a novel construction method to install construction materials with robot on construction site. Seung Yeol Lee received the B.S. degree from the Department of Mechanical Engineering, Myungji University, Seoul, Korea in 2002, and the M.S. degree from the Department of Mechatronics Engineering, Hanyang University, Seoul, Korea in 2005. He is a Ph.D. degree candidate from the Department of Mechanical Engineering, Hanyang University, Seoul, Korea. From 2003, He is currently a visiting researcher in the Research Institute of Technology, Construction Group at the Samsung Corporation, Korea conducting the design and implementation of construction robot and automation system for construction project. His research interests include design, control, and application of construction robots, field robotic systems and ergonomic design of robotic systems. He is a member of the Korea Society of Mechanical Engineers, Architectural Institute of Korea, and Ergonomics Society of Korea. Yong Seok Lee received the B.S. degree from the Department of Precision Mechanical Engineering, Kunsan national University, Kunsan, Korea in 2002, and the M.S. degree from the Department of Precision Mechanical Engineering, Hanyang University, Seoul, Korea in 2005. Currently, he is the Post Master in Hanyang University, Korea. His major interests include design and kinematic/dynamic analysis on multi-purpose field robots and service robots. He is a member of the Architectural Institute of Korea. Bum Seok Park received the B.S. degree from the Department of Mechanical Engineering, Hanyang University, Ansan, Kyung-gi Do, Korea in 1993, and the M.S. degree from the Department of Mechatronics Engineering, Hanyang University, Seoul, Korea in 1998. He is a Ph.D. from the Department of Mechatronics System Engineering, Hanyang University, Seoul, Korea From 2006. He is currently the post-doctor in Hanyang University, Korea. His major interests include embedded robot control system on multi-purpose field robot and service robot. He is a member of the Korea Society of Mechanical Engineers, Korean Society of Machine Tool Engineers. Sang Heon Lee graduated with the B.S. degree in Precision Mechanical Engineering from Hanyang University, Seoul, Korea in 1992. He received the M.S. degree in Precision Engineering from KAIST, Taejon, Korea in 1994 and the Ph.D. degree in Mechanical Engineering from KAIST in 2001. Currently, he is a senior researcher in Samsung Corporation, Korea. His major interests include the kinematic/dynamic analysis on multi-body system, application of field robots, and automation in construction. ChangSoo Han received the B.S. degree from the Department of Mechanical Engineering, Seoul National University Technology, Seoul, Korea in 1983, and the M.S. and Ph.D. degrees from the Department of Mechanical Engineering, University of Texas at Austin, in 1985 and 1989, respectively. From May 1988 to September 1989, he was a Research Assistant, Robotics Lab in Mechanical Engineering about manufacturing of the high resolution micro manipulator module. In March 1990, he joined Hanyang University, Ansan, Kyungki-Do, Korea as a Professor, Department of Mechanical Engineering. From March 1993 to February 1995, he was a Vice President, The Research Institute of Engineering & Technology of the Hanyang University. From August 1996 to July 1997, he was a Visiting Professor, Univ. of California at Berkeley. From September 1997 to February 1999, he was a Director, Hanyang Business Incubator. In August 2000, he joined a Branch President, The Korean Society of Mechanical Engineers. In January 2002, he joined a Committee Member, The Korean Society of Mechanical Engineers. From January 2001 to December 2001, he was an International Cooperation Director, The Institute of Control, Automation and Systems, Korea. His research interests include design, control, and application of robot, automation systems, and advanced vehicle.     

Hybrid control of a two-arm robot for complex tasks

For many coordinated tasks, a two-arm robot cannot be properly controlled by using a simple position control scheme and therefore requires a certain form hybrid control. Uchiyama and Dauchez recently proposed a symmetric hybrid position/force scheme for the manipulation of rigid objects rigidly held. The main results of this theory are summarized in this paper, and the limitations are pointed out. Several examples in which the relative motion of the end effectors cannot be neglected are presented: manipulation of rigid objects non-rigidly held, deformation of a flexible object, and assemblies of two objects “in space”. These tasks are analyzed and attempted control schemes are given for each of them. The dynamic effects are always neglected in this preliminary theoretical approach. An experimental setup built around two six axis PUMA arms and a parallel processing controller has been installed in order to validate our theoretical results. The hardware and software of this setup are also briefly described in this paper.     

Impedance control with on-line neural-network compensator for robot contact tasks

In this paper, a force-tracking impedance controller with an on-line neural-network compensator is shown to be able to track a reference force in the presence of unknown environmental dynamics. The controller can be partitioned into three parts. The computed torque method is used to linearize and decouple the dynamics of a manipulator. An impedance controller is then added to regulate the mechanical impedance between the manipulator and its environment. In order to track a reference force signal, an on-line neural network is used to compensate the effect of unknown parameters of the manipulator and environment.     

Haptic force control based on impedance/admittance control aided by visual feedback

This paper demonstrates a haptic device for interaction with a virtual environment. The force control is added by visual feedback that makes the system more responsive and accurate. There are two popular control methods widely used in haptic controller design. First, is impedance control when user motion input is measured, and then, the reaction force is fed back to the operator. The alternative method is admittance control, when forces exerted by user are measured and motion is fed back to the user. Both, impedance and admittance control are also basic ways for interacting with a virtual environment. In this paper, several experiments were performed to evaluate the suitability of force-impedance control for haptic interface development. The difference between conventional application of impedance control in robot motion control and its application in haptic interface development is investigated. Open loop impedance control methodology is implemented for static case and a general-purpose robot under open loop impedance control was developed as a haptic device, while a closed loop model based impedance control was used for haptic controller design in both static and dynamic case. The factors that could affect to the performance of a haptic interface are also investigated experimentally using parametric studies. Experimental results for 1 DOF rotational motion and 2 DOF planar translational motion systems are presented. The results show that the impedance control aided by visual feedback broaden the applicability of the haptic device and makes the system more responsive and accurate.

基于IMU的主动伴舞机器人人机协作控制算法

提出了基于惯性测量单元IMU的主动型伴舞机器人人机协作控制算法。机器人腰部安装具有一定刚度的弹簧,利用Kalman滤波将三轴加速度计数据与三轴陀螺仪数据进行融合,得到机器人在人类舞伴作用下的姿态角变化,采用阈值法滤除相对姿态角抖动误差,再结合当前机器人状态,综合判断得到相对姿态角到速度矢量的映射。将期望轨迹速度与人力产生的轨迹修正速度融合,得到人机协作下机器人的运动轨迹和剩余目标点的坐标修正值。将算法应用于华尔兹CCL舞步轨迹测试,实验结果表明算法效果良好。     

Implementation of robust impedance and force control

In this paper, we discuss the problem of implementing impedance control in the presence of model uncertainties and its application to robot force control. We first propose a sliding mode-based impedance controller. The implementation of the targeted impedance, and the preservation of stability in the presence of model uncertainties, are the key issues in the proposed approach. Using sliding mode control, a simple and robust algorithm is obtained so that the targeted impedance can be accurately implemented without the exact model of the robot. The controller is designed in terms of the task space coordinates. The chattering in the sliding mode control is eliminated by using a continuous function. The problem of force control is also addressed for the impedance controlled robot. An off-line estimation method of the environment model is suggested and used in the force control scheme. The proposed impedance and force control schemes have been experimentally verified on a two degree-of-freedom direct-drive robot arm. The experimental results are presented in this paper.     

Edge-cloud cooperation driven self-adaptive exception control method for the smart factory

Production exceptions often occur due to the uncertainties of resources such as random machine broken, urgent production tasks. The timely identification and optimal control of the production exceptions are the core issues to ensure the reliable operation of smart manufacturing system. However, due to the evolution mechanism of uncertain factor is hard to describe, and the current cloud-based production analysis and decision-making mode often requires a long processing time. As a result, the extraction of abnormal events often delays and the optimal control decisions are hard to made. To meet this issue, an edge-cloud cooperation driven self-adaptive exception control method is proposed for the smart factory. Firstly, the advanced industrial Internet of things and embedded edge-computing technologies are applied to create an intelligent environment where the resources are made smart with the ability of self-sensing, self-analytics and self-optimization. Then, the fuzzy Bayesian network is used to extract the production exceptions and diagnose their causes, where fuzzy sets are used to describe the production status. After that, a self-adaptive production exception handling method is involved through an edge-cloud cooperation mechanism. The machines will adjust their production parameters at first, and then the horizontal collaboration among machines at same production level and vertical cooperation between different production levels will be used to deal with exceptions self-adaptively. Lastly, a case from casting post-processing system is used to demonstrate the proposed method, and results show that the proposed method can largely improve the production efficiency.     

Force feedback control design for nonideal teleoperators

Achieving force feedback for a nonideal teleoperator is challenging, due to complications such as friction, force sensor noise, non-backdriveability and structural resonances. Furthermore, non-collocation of the force sensors and the point of interaction results in shunt dynamics that degrade the interaction force estimation. In this paper, a method is presented to model, identify and compensate for the influence of shunt dynamics. Furthermore, a recently developed two-layer approach that enforces passivity in the time domain is implemented and evaluated in a practical setup that is dedicated for application in surgery. Experiments demonstrate that using a combination of these techniques with an impedance reflecting controller, stable bilateral interaction with both soft and hard environments is achieved, for a nonideal system. A teleoperated robot for minimally invasive surgery is used as a representative example of a nonideal surgical system.     

基于阻抗模型的下肢康复机器人交互控制系统设计

为帮助下肢功能障碍患者进行康复训练,设计了下肢康复机器人。对于该机器人的控制,采用传统系统无法柔顺控制,导致机器人运动轨迹偏离预设轨迹。针对该现象,提出了基于阻抗模型的下肢康复机器人交互控制系统设计。通过分析总体控制方案,设计系统硬件结构框图。采用L型二维力传感器,确定两个方向的人机交互力。使用绝对值编码器安装在各个关节处,其输出值作为髋关节、膝关节、踝关节电机的转动位置,增量编码器安装在电机轴上,测量值用来作为后期控制方法的输入参数。构建阻抗控制模型,能够调节机器人位置和速度,具有消除力误差功能。依据此力矩对参考运动轨迹进行设计,实时获取患者康复训练的跟踪、主动柔顺和接近状态信息。在柔顺训练实验测出人机交互力,通过实验结果知,在检测到人体主动力矩异常时,系统能够重新优化轨迹,具有良好柔顺控制效果。     

移动机器人编队控制的现状与问题

随着机器人向系统应用的方向发展，移动机器人编队控制问题成为研究的热点问题．为此，依据解决编队控制问题的不同思路，总结了编队控制的各种研究方法：基于行为法、人工势场法、跟随一领航法、虚结构法、循环法、模型预测控制法、分布式控制法，分别对几种编队控制方法的基本思想和特点进行总结和分析，最后从通用性、稳定性、鲁棒性和安全性等方面阐述了移动机器人编队控制理论与应用方面有待进一步研究的几个主要问题。     

Model reference adaptive impedance control for physical human-robot interaction

This paper presents a novel enhanced human-robot interaction system based on model reference adaptive control. The presented method delivers guaranteed stability and task performance and has two control loops. A robot-specific inner loop, which is a neuroadaptive controller, learns the robot dynamics online and makes the robot respond like a prescribed impedance model. This loop uses no task information, including no prescribed trajectory. A task-specific outer loop takes into account the human operator dynamics and adapts the prescribed robot impedance model so that the combined human-robot system has desirable characteristics for task performance. This design is based on model reference adaptive control, but of a nonstandard form. The net result is a controller with both adaptive impedance characteristics and assistive inputs that augment the human operator to provide improved task performance of the human-robot team. Simulations verify the performance of the proposed controller in a repetitive point-to-point motion task. Actual experimental implementations on a PR2 robot further corroborate the effectiveness of the approach.     

A review for control theory and condition monitoring on construction robots

The application of robotic technologies in building construction leads to great convenience and productivity improvement, and construction robots (CRs) bring enormous opportunities for the way we conduct design and construction. To get a better understanding of the trends and track the application of CRs for on-site conditions, this paper conducts a systematic review of control models and status monitoring of CRs, which are two key aspects that determine construction accuracy and efficiency. Control accuracy and flexibility are primary needs for CRs applied in different scenes, so the control methods based on driving models are vitally important. Status monitoring on CRs contains knowledge in fault detection, intelligence maintenance, and fault-tolerant control, and multiple objectives need to be met and optimized in the whole drive chain. Moreover, the state-of-the-art is comprehensively summarized, and new insights are also provided to carry on promising researches.     

基于D-H法的农业采摘机器人运动协作控制系统设计

为提升农业采摘机器人运动协作控制性能,降低机器人碰撞概率,利用D-H法优化设计机器人运动协作控制系统。改装位置、力矩以及碰撞传感器设备,优化运动协作控制器与驱动器,调整系统通信模块结构,完成硬件系统的优化。利用D-H法构建农业采摘机器人数学模型,在该模型下,利用传感器设备实现机器人实时位姿的量化描述,通过机器人采摘流程的模拟,分配机器人运动协作任务,从位置和姿态等多个方面,确定运动协作控制目标,经过受力分析求解机器人实际作用力,最终通过控制量的计算,实现农业采摘机器人的运动协作控制功能。通过系统测试实验得出结论：与传统控制系统相比,机器人位置、姿态角和作用力的控制误差分别降低了约40mm、0.2°和1.2N,在优化设计系统控制下,机器人的碰撞次数得到明显降低。     

实时以太网系统中控制与通信的协同调度方法

为了提高实时以太网系统的运行效率和通信实时性,在EPA（Ethernet for Plant Automation）确定性通信调度的基础上,提出了控制与通信的协同调度方法。该方法将EPA设备的通信宏周期划分成通信时间片和控制时间片,在系统中设置定时器,在通信时间片或控制时间片到达时,由定时器引发中断,在执行中断处理程序时获取当前时间,根据当前时间位于通信时间片内或控制时间片内来分别执行通信任务或控制任务。实验结果表明,该方法能够有效避免功能块的无效执行和数据的无效传输,提高系统的运行效率和通信实时性能。     

Intelligent text recognition based on multi-feature channels network for construction quality control

Construction quality control is achieved primarily through various testing and inspections and subsequent analysis of the massive unstructured quality records. The quality professionals are required to classify and review the inspection texts according to the project category. However, manual processing of a sheer amount of textual data is not only time-consuming, laborious but also error-prone, which could lead to overlooked quality issues and harm the overall project performance. In response, this paper uses the text mining method to mine the hidden information from unstructured text records. First, obtain quality text records on-site, use data cleaning method to obtain 9859 clean data, then use both Bidirectional Encoder Representation from Transformers (BERT) pre-training and Word2vec methods to quantify the text into a digital representation, next improve the Convolutional Neural Network (CNN) model by expanding input channels, and input the quantified text into the model to extract key features to realize the integration of quality records according to established categories. The results show that the average precision of the proposed model is 89.69%. Compared with CNN, BERT, and other models, this model has less manual intervention, less time-consuming training, and higher precision. Finally, through data augmentation of small sample data, the precision of the model is further improved, reaching 92.02%. The proposed model can assist quality professionals to quickly spot key quality issues and reference corresponding quality standards for further actions, and allow them to focus on more value-added efforts, e.g., making decisions and planning for corrective actions. This research also provides a reference for the ultimate goal of constructing an intelligent project management system.     

Thermal image-based hand gesture recognition for worker-robot collaboration in the construction industry: A feasible study

Worker-robot collaboration (WRC) is a promising solution for complex construction tasks, which can integrate the robots’ advantages in strength and accuracy with human ability in intuitive decision-making and adaptability. A new imperative objective for real-world WRC is to design a user-friendly interface to support safe and efficient worker-robot interactions. Vision-based hand gesture is a simple but effective solution. However, existing methods mainly depend on 3-channel RGB images captured by visible cameras, which are prone to be affected by on-site environmental disturbances, such as poor illumination, fog, and dust. Moreover, previous networks strive for high accuracy, neglecting computational efficiency (e.g., model size and latency) when implementing the network on resource-constrained devices like mobile construction robots. Against this backdrop, this research presented a feasibility study to investigate whether hand signals can be detected from thermal images and designed a lightweight network that has fewer parameters and obtains lower latency without compromising accuracy. Experimental results indicated that thermal images were robust to different lighting conditions, and the proposed model achieved a high classification accuracy (97.54 %) with 1.8 M parameters. The comparative study demonstrated the superiority of our model to other advanced lightweight models, illustrating the feasibility of the developed method in supporting safe WRC applications by recognizing workers’ hand signals.     

Design and construction of the cooperation support agent for face-to-face class and e-learning

E-learning study mainly helps acquisitions of knowledge. However, the effect acquired from dialog on a face-to-face class is not expectable. Thus, Blended-learning which combined a face-to-face class and e-learning attracts attention. Although the blend of ideal Blended-learning should be used by learners on consideration of their capabilities and learning records, the realization is difficulty. In this paper, we proposed and built a mobile agent system which offers cooperation support with a face-to-face class and e-learning. The mobile agents operating autonomously indicate the learner＇s weak points and contents which should be learned from a learning plan （learning policy） given by the contents creator and a personal learning record. Therefore, the mobile agents can support the Blended-learning by creating the personal learning result data in consideration of personal capability and personal learning records.     

多预警机情报协同任务控制研究*

对多预警机情报协同任务分配和任务协调问题展开研究。首先,结合集中式任务控制方式和分布式控制方式的优点,设计了混合式任务控制体系结构,以支持在主指挥机的监控下实现不同级别上的任务自主分配;其次,在通过合同网实现动态任务分配的基础上,建立转包合同机制对任务执行过程进行协调,提高了多预警机情报协同的整体效能。仿真结果表明了该方法的有效性。     

A framework and method for Human-Robot cooperative safe control based on digital twin

Human-robot collaboration (HRC) combines the robot’s mechanical properties and predictability with human experience, logical thinking, and strain capabilities to alleviate production efficiency. However, ensuring the safety of the HRC process in-real time has become an urgent issue. Digital twin extends functions of virtual models in the design phase of the physical counterpart in the production phase through virtual-real interactive feedback, data fusion analysis, advanced computational features, etc. This paper proposes an HRC safety control framework and corresponding method based on the digital twin. In the design phase, virtual simulation and virtual reality technology are integrated to construct virtual twins of various HRC scenarios for testing and analyzing potential safety hazards. In the production phase, the safety distance between humans and robots of the HRC scene is monitored and calculated by an iterative algorithm according to machine vision and a convolutional neural network. Finally, the virtual twin is driven based on real-scene data, real-time online visual monitoring, and optimization of the HRC’s overall process. A case study using ABB-IRB1600 is presented to verify the feasibility of the proposed approach.