机器人技术在图书馆自动化系统中的应用研究

随着计算机技术的发展,图书馆的信息管理已经实现了自动化,但其自动存取技术仍然落后。旋转柜、自动柜有限地实现了存取操作自动化;自动仓储式图书馆以及可实现自动存取操作的图书馆移动机器人系统是目前研究的新动向。本文在分析这些系统的原理及优缺点基础上,指出能实现自动存取操作的移动机器人系统是最适合于图书文档管理的系统,而针对图书馆自动存取操作的特殊场合,研制功能适合于图书馆书籍操作的机械手,是图书馆机器人技术的瓶颈。     

Advancements of the KUCIM automated flexible manufacturing workstation

Incremental automation, i.e. adding capabilities over time, is an alternative for small mannfacturers to large scale automation projects as a method of achieving automated manufacturing. As an example of incremental automation, the University of Kansas Computer Integrated Manufacturing (KUCIM) workstation has developed over time into an unmanned flexible machining workstation. Presently, the workstation contains a Hurco three-axis milling machine, an American Robot six-axis robot, a Sun 4/260, a versatile fixturing system, an IBM PC-AT compatible computer, and an interface between the milling machine and PC. The control architecture is based on the National Institute for Standards and Technology (NIST) Automated Manufacturing Research Facility (AMRF) manufacturing control hierarchy. The workstation controller employs three software modules: the Supervisor, the Robot Foreman, and the Fixture/Machine Tool Foreman. At the equipment level, two modules are used: the Robot Command Interpreter and the Fixture/Machine Tool Command Interpreter. The three functions that the KUCIM workstation performs to produce parts are: processing an input file, performing tool zeroing and performing machining cycles.     

基于强化学习的机器人多接触交互任务控制

作为自动化和智能化时代的代表,机器人技术的发展成为智能控制领域研究的焦点,各种基于机器人的智能控制技术应运而生,机器人被越来越多地应用于实现与环境之间的复杂多接触交互任务.本文以机器人复杂多接触交互任务为核心问题展开讨论,结合基于强化学习的机器人智能体训练相关研究,对基于强化学习方法实现机器人多接触交互任务展开综述.概述了强化学习在机器人多接触任务研究中的代表性研究,当前研究中存在的问题以及改进多接触交互任务实验效果的优化方法,结合当前研究成果和各优化方法特点对未来机器人多接触交互任务的智能控制方法进行了展望.     

Present and future robot control development—An industrial perspective

Robot control is a key competence for robot manufacturers and a lot of development is made to increase robot performance, reduce robot cost and introduce new functionalities. Examples of development areas that get big attention today are multi robot control, safe control, force control, 3D vision, remote robot supervision and wireless communication. The application benefits from these developments are discussed as well as the technical challenges that the robot manufacturers meet. Model-based control is now a key technology for the control of industrial robots and models and control schemes are continuously refined to meet the requirements on higher performance even when the cost pressure leads to the design of robot mechanics that is more difficult to control. Driving forces for the future development of robots can be found in, for example, new robot applications in the automotive industry, especially for the final assembly, in small and medium size enterprises, in foundries, in food industry and in the processing and assembly of large structures. Some scenarios on future robot control development are proposed. One scenario is that light-weight robot concepts could have an impact on future car manufacturing and on future automation of small and medium size enterprises (SMEs). Such a development could result in modular robots and in control schemes using sensors in the robot arm structure, sensors that could also be used for the implementation of redundant safe control. Introducing highly modular robots will increase the need of robot installation support, making Plug and Play functionality even more important. One possibility to obtain a highly modular robot program could be to use a recently developed new type of parallel kinematic robot structure with large work space in relation to the robot foot print. For further efficient use of robots, the scenario of adaptive robot performance is introduced. This means that the robot control is optimised with respect to the thermal and fatigue load on the robot for the specific program that the robot performs. The main conclusion of the presentation is that industrial robot development is far away from its limits and that a lot of research and development is needed to obtain a more widely use of robot automation in industry.     

A Non-Time Based Controller for Load Swing Damping and Path-Tracking in Robotic Cranes

This paper proposes the use of the non-time based control strategy named Delayed Reference Control (DRC) to the control of industrial robotic cranes. Such a control scheme has been developed to achieve two relevant objectives in the control of autonomous operated cranes: the active damping of undesired load swing, and the accurate tracking of the planned path through space, with the preservation of the coordinated Cartesian motion of the crane. A paramount advantage of the proposed scheme over traditional ones is its ease of implementation on industrial devices: it can be implemented by just adding an outer control loop (incorporating path planning) to standard position controllers. Experimental performance assessment of the proposed control strategy is provided by applying the DRC to the control of the oscillation of a cable-suspended load moved by a parallel robot mimicking a robotic crane. In order to implement the DRC scheme on such an industrial robot it has been just necessary to manage path planning and the DRC algorithm on a separate real-time hardware computing the delay in the execution of the desired trajectory suitable to reduce load swing. Load swing has been detected by processing the images from two off-the-shelf cameras with a dedicated vision system. No customization of the robot industrial controller has been necessary.     

Learning Control of Robot Manipulators in Task Space

Two important properties of industrial tasks performed by robot manipulators, namely, periodicity (i.e., repetitive nature) of the task and the need for the task to be performed by the end‐effector, motivated this work. Not being able to utilize the robot manipulator dynamics due to uncertainties complicated the control design. In a seemingly novel departure from the existing works in the literature, the tracking problem is formulated in the task space and the control input torque is aimed to decrease the task space tracking error directly without making use of inverse kinematics at the position level. A repetitive learning controller is designed which “learns” the overall uncertainties in the robot manipulator dynamics. The stability of the closed‐loop system and asymptotic end‐effector tracking of a periodic desired trajectory are guaranteed via Lyapunov based analysis methods. Experiments performed on an in‐house developed robot manipulator are presented to illustrate the performance and viability of the proposed controller.     

An Overview of Calibration Technology of Industrial Robots

With the continuous improvement of automation,industrial robots have become an indispensable part of automated production lines.They widely used in a number of industrial production activities,such as spraying,welding,handling,etc.,and have a great role in these sectors.Recently,the robotic technology is developing towards high precision,high intelligence.Robot calibration technology has a great significance to improve the accuracy of robot.However,it has much work to be done in the identification of robot parameters.The parameter identification work of existing serial and parallel robots is introduced.On the one hand,it summarizes the methods for parameter calibration and discusses their advantages and disadvantages.On the other hand,the application of parameter identification is introduced.This overview has a great reference value for robot manufacturers to choose proper identification method,points further research areas for researchers.Finally,this paper analyzes the existing problems in robot calibration,which may be worth researching in the future.     

A cable feeder tool for robotized cable winding

Cable winding is an alternative technology to create stator windings in large electrical machines. Today such cable winding is performed manually, which is very repetitive, time-consuming and therefore also expensive. This paper presents the design, function and control system of a developed cable feeder tool for robotized stator cable winding. The presented tool was able to catch a cable inside a cable guiding system and to grab the cable between two wheels. One of these wheels was used to feed cable through the feeder. A control system was integrated in the tool to detect feeding slippage and to supervise the feeding force on the cable. Functions to calculate the cable feed length, to release the cable from the tool and for positional calibration of the stator to be wound were also integrated in the tool. In validating the function of the cable feeder tool, the stator of the linear generator used in the Wave Energy Converter generator developed at Uppsala University was used as an example. Through these experiments, it was shown that the developed robot tool design could be used to achieve automated robotized cable winding. These results also complied with the cycle time assumptions for automated cable winding from earlier research. Hence, it was theoretically indicated that the total winding cycle time for one Uppsala University Wave Energy Converter stator could be reduced from about 80 h for manual winding with four personnel to less than 20 h in a fully developed cable winding robot cell. The same robot tool and winding automation could also be used, with minor adjustments, for other stator designs.     

Trust in automation: Part I. Theoretical issues in the study of trust and human intervention in automated systems

Abstract

Today many systems are highly automated. The human operator's role in these systems is to supervise the automation and intervene to take manual control when necessary. The operator's choice of automatic or manual control has important consequences for system performance, and therefore it is important to understand and optimize this decision process. One important determinant of operators' choice of manual or automatic control may be their degree of trust in the automation. However, there have been no experimental tests of this hypothesis until recently, nor is there a model of human trust in machines to form a theoretical foundation for empirical studies. In this paper a model of human trust in machines is developed, taking models of trust between people as a starting point, and extending them to the human-machine relationship. The resulting model defines human trust in machines and specifies how trust changes with experience on a system, providing a framework for experimental research on trust and human intervention in automated systems.     

Semi-autonomous shared control of large-scale manipulator arms

Semi-autonomous operation with shared control between the human operator and control computer has been developed and examined for a large-scale manipulator for gripping and lifting heavy objects in unstructured dynamical environments. The technique has been implemented on an electro-hydraulic actuated crane arm with redundant kinematic structure. Several modes of automation and interaction were evaluated. Experiments show satisfactory smoothness in the transitions between autonomous, shared and manual control, doubled performance in log loading for inexperienced operators while experienced operators reported reduced workload.     

Fuzzy Logic Decision Mechanism Combined with a Neuro-Controller for Fabric Tension in Robotized Sewing Process

A new approach for flexible automated handling of fabrics in the sewing process is described, which focuses to control the cloth tension applied by a robot. The proposed hierarchical robot control system includes a Fuzzy decision mechanism combined with a Neuro-controller. The expert's actions during the sewing process are investigated and this human behavior is interpreted in order to design the controller. The Fuzzy Logic decision mechanism utilizes only qualitative knowledge concerning the properties of the fabrics, in order to determine the desired tensional force and the location of the robot hand on the fabric. A Neural Network controller regulates the fabric tension to achieve the desired value by determining the robot end effector velocity. The simulation results demonstrate the efficiency of the system as well as the robustness of the controller performance since the effects of the noise are negligible. The system capabilities are more evident when the controller uses its previously acquired experience.     

Vision-based intelligent control for automated assembly

Development of an automated assembly system requires integration of different engineering modules and coordination of interactions between these modules. This paper presents some of the results of an effort in developing an assembly automation schene for an automated work cell. Integration of the control scheme with the vision module and an on-line trajectory planner is presented. Special characteristics of this automation scheme are dynamic integration of vision and feedback control, real-time operation, uncertainty compensation and error recovery. The hardware required for implementation of this scheme is described. Results of implementing this scheme on a PUMA robot performing a carburetor and gasket mating operation are presented.     

A Study on Development of a Hybrid Aerial/Terrestrial Robot System for Avoiding Ground Obstacles by Flight

To date, many studies related to robots have been performed around the world. Many of these studies have assumed operation at locations where entry is difficult, such as disaster sites, and have focused on various terrestrial robots, such as snake-like, humanoid, spider-type, and wheeled units. Another area of active research in recent years has been aerial robots with small helicopters for operation indoors and outdoors. However, less research has been performed on robots that operate both on the ground and in the air. Accordingly, in this paper, we propose a hybrid aerial/terrestrial robot system. The proposed robot system was developed by equipping a quadcopter with a mechanism for ground movement. It does not use power dedicated to ground movement, and instead uses the flight mechanism of the quadcopter to achieve ground movement as well. Furthermore, we addressed the issue of obstacle avoidance as part of studies on autonomous control. Thus, we found that autonomous control of ground movement and flight was possible for the hybrid aerial/terrestrial robot system, as was autonomous obstacle avoidance by flight when an obstacle appeared during ground movement.      

A Real Time Self-Tuning Motion Controller for Mobile Robot Systems

This paper proposes an intelligent controller for motion control of robotic systems to obtain high precision tracking without the need for a real-time trial and error method. In addition, a new self-tuning algorithm has been developed based on both the ant colony algorithm and a fuzzy system for real-time tuning of controller parameters. Simulations and experiments using a real robot have been addressed to demonstrate the success of the proposed controller and validate the theoretical analysis. Obtained results confirm that the proposed controller ensures robust performance in the presence of disturbances and parametric uncertainties without the need for adjustment of control law parameters by a trial and error method.      

Robust Tracking Control for Self-balancing Mobile Robots Using Disturbance Observer

In this paper, a robust tracking control scheme based on nonlinear disturbance observer is developed for the self-balancing mobile robot with external unknown disturbances. A desired velocity control law is firstly designed using the Lyapunov analysis method and the arctan function. To improve the tracking control performance, a nonlinear disturbance observer is developed to estimate the unknown disturbance of the self-balancing mobile robot. Using the output of the designed disturbance observer, the robust tracking control scheme is presented employing the sliding mode method for the selfbalancing mobile robot. Numerical simulation results further demonstrate the effectiveness of the proposed robust tracking control scheme for the self-balancing mobile robot subject to external unknown disturbances.      

SMA驱动的微型平面关节机器人的研究

近年来，利用形状记忆合金（ＳＭＡ）的形状记忆效应原理制作的驱动器已在机器人领域中得到应用，ＳＭＡ驱动器以其重量轻、结构紧凑、易控制等优点，大大推动了微型机器人的发展．本课题使用所研制的推挽式直线位移型和旋转关节型ＳＭＡ驱动器代替传统的伺服驱动系统，研制了一台三自由度（两个旋转自由度和一个直线自由度）且带末端夹持器的微型平面关节机器人．本文将介绍该机器人的结构设计，控制系统及其软件设计．     

谈工业生产现场中的计算机自动控制技术

近几年来,我国计算机自动化控制技术发展速度较快,一些大型企业和工厂已经普遍引进生产设备,提高了生产效率,扩大了自动化生产能力。随着科技的发展,生产现场数据采集及自动化控制已经无法满足日益增长的物质文化需求,这需要计算机管理人员专针对不同的需求,引进不同的、适合企业发展的新自动化技术。     

Robust Sliding Control of Robotic Manipulators Based on a Heuristic Modification of the Sliding Gain

A task space robust trajectory tracking control is developed for robotic manipulators. A second order linear model, which defines the desired impedance for the robot, is used to generate the reference position, velocity and acceleration trajectories under the influence of an external force. The control objective is to make the robotic manipulator’s end effector track the reference trajectories in the task space. A sliding mode based robust control is used to deal with system uncertainties and external perturbations. Thus, a sliding manifold is defined by a linear combination of the tracking errors of the system in the task space built from the difference between the real and the desired position, velocity and acceleration trajectories in comparison with previous works where the sliding manifold was defined by the desired impedance and the external force. Moreover, the ideal relay has been substituted by a relay with a dead-zone in order to fit in with the actual way in which a real computational device implements the typical sign function in sliding mode control. Furthermore, a higher level supervision algorithm is proposed in order to reduce the amplitude of the high frequency components of the output associated to an overestimation of the system uncertainty bounds. Then, the robust control law is applied to the case of a robot with parametric uncertainty and unmodeled dynamics. The closed-loop system is proved to be robustly stable with all signals bounded for all time while the control objective is fulfilled in practice. Finally, a simulation example which shows the usefulness of the proposed scheme is presented.     

Quay crane scheduling in automated container terminal for the trade-off between operation efficiency and energy consumption

At present, the automation of handling equipment has changed the operation mode in the automated container terminal. This paper investigates the automated quay crane scheduling problem (AQCSP) for the automated container terminal. The operation process of AQCSP is decomposed, and formulated it as a mixed integrated programming model. In the numerical experiments, the relation between operation efficiency and energy consumption has been quantitative analyzed by case study. Moreover, the sensitivity analysis of the ratios for all tasks in a vessel bay and the tasks in each stack are also presented. The findings of this study will provide a theoretical reference for the study on the trade-off operation efficiency and energy consumption on the operational level.     

An Architecture for Human‐Guided Autonomy: Team TROOPER at the DARPA Robotics Challenge Finals

Recent robotics efforts have automated simple, repetitive tasks to increase execution speed and lessen an operator's cognitive load, allowing them to focus on higher‐level objectives. However, an autonomous system will eventually encounter something unexpected, and if this exceeds the tolerance of automated solutions, there must be a way to fall back to teleoperation. Our solution is a largely autonomous system with the ability to determine when it is necessary to ask a human operator for guidance. We call this approach human‐guided autonomy. Our design emphasizes human‐on‐the‐loop control where an operator expresses a desired high‐level goal for which the reasoning component assembles an appropriate chain of subtasks. We introduce our work in the context of the DARPA Robotics Challenge (DRC) Finals. We describe the software architecture Team TROOPER developed and used to control an Atlas humanoid robot. We employ perception, planning, and control automation for execution of subtasks. If subtasks fail, or if changing environmental conditions invalidate the planned subtasks, the system automatically generates a new task chain. The operator is able to intervene at any stage of execution, to provide input and adjustment to any control layer, enabling operator involvement to increase as confidence in automation decreases. We present our performance at the DRC Finals and a discussion about lessons learned.