Service Platform for Robotic Disassembly Planning in Remanufacturing

Remanufacturing is being paid much attention due to environmental protection and resource re-utilization. Disassembly is an inevitable step of remanufacturing and it is always finished by the manual labor. Robotic disassembly helps to improve the automation of disassembly process, while robotic disassembly planning helps to improve the efficiency of robotic disassembly. However, the existing research on robotic disassembly planning seldom integrates the physical industrial robots and then provides convenient services for the users. In this paper, the framework of service platform for robotic disassembly planning in remanufacturing is studied. The database of the service platform is designed, and the data communication method between the software system and KUKA industrial robots is studied. After that, based on the physical facilities, this service platform is implemented using MyEclipse software. The developed service platform is convenient for the users to access the methods of robotic disassembly planning and the connected industrial robots can also execute the optimal disassembly solutions through the data communication method after the optimal disassembly solutions are obtained. Finally, case study based on an idler shaft is conducted to verify the developed service platform for robotic disassembly planning.     

A Fuzzy Qualitative Framework for Connecting Robot Qualitative and Quantitative Representations

This paper proposes a novel framework for describing articulated robot kinematics motion with the goal of providing a unified representation by combining symbolic or qualitative functions and numerical sensing and control tasks in the context of intelligent robotics. First, fuzzy qualitative robot kinematics that provides theoretical preliminaries for the proposed robot motion representation is revisited. Second, a fuzzy qualitative framework based on clustering techniques is presented to connect numerical and symbolic robot representations. Built on the $k-{{bb AGOP}}$ operator (an extension of the ordered weighted aggregation operators), k-means and Gaussian functions are adapted to model a multimodal density of fuzzy qualitative kinematics parameters of a robot in both Cartesian and joint spaces; on the other hand, a mixture regressor and interpolation method are employed to convert Gaussian symbols into numerical values. Finally, simulation results in a PUMA 560 robot demonstrated that the proposed method effectively provides a two-way connection for robot representations used for both numerical and symbolic robotic tasks.      

机器人的鲁棒预测控制

本文提出基于误差预测的机器人鲁棒控制器。考虑到机器人的动力学建模误差影响其控制性能,本文建立机器人的误差模型,给出预测建模误差对运动轨迹偏差的作用的有效方法,并提出建模误差的鲁棒性补偿。本文分别在关节空间和直角空间针对冗余机器人和非冗余机器人提出鲁棒预测控制器设计,其有效性由仿真例子检验。     

Skill learning framework for human–robot interaction and manipulation tasks

In this article, a learning framework that enables robotic arms to replicate new skills from human demonstration is proposed. The learning framework makes use of online human motion data acquired using wearable devices as an interactive interface for providing the anticipated motion to the robot in an efficient and user-friendly way. This approach offers human tutors the ability to control all joints of the robotic manipulator in real-time and able to achieve complex manipulation. The robotic manipulator is controlled remotely with our low-cost wearable devices for easy calibration and continuous motion mapping. We believe that our approach might lead to improving the human-robot skill learning, adaptability, and sensitivity of the proposed human-robot interaction for flexible task execution and thereby giving room for skill transfer and repeatability without complex coding skills.     

Functional Modeling for Monitoring of Robotic System

With the expansion of robotic applications in the industrial domain, it is important that the robots can execute their tasks in a safe and reliable way. A monitoring system can be implemented to ensure the detection of abnormal situations of the robots and report the abnormality to their human supervisors or cooperators. In this work, we focus on developing a modeling framework for monitoring robotic system based on means-end analysis and the concept of action phases from action theory. A circular cascaded action phase structure is proposed for building the model of cyclical robotic events. This functional model provide a formal way of decompose robotic tasks and analyze each level of conditions for an action to be executed successfully. It can be used for monitoring robotic systems by checking the preconditions in the action phases and identifying the failure modes. The proposed method is demonstrated by using a simulated robotic manipulation system. The simulation results demonstrate the feasibility of the developed functional model in finding errors during the execution monitoring.     

基于向量空间的Web服务发现模糊方法

Web服务已逐渐发展成为重要的分布式计算范式。在综合分析了现有的Web服务描述文档的基础上,提出了一种基于模糊集的服务特征项集选取算法以及Web服务向量空间的生成方法。利用生成的向量空间,对Web服务进行模糊聚类。基于此,文中给出了向量空间中进行Web服务发现的模糊方法。所提出的方法只需利用现有的Web服务描述信息,保证了服务发现的有效性。     

Evolutionary design framework for Smart PSS: Service engineering approach

Digital technology is transforming industry, economy, and society. Under this digitalization trend, a new concept of product and service offerings, Smart PSS has been introduced. While the Smart PSS concept aiming at data-driven innovation attracts more attentions, there are two major challenges in designing Smart PSS. First, available data from digital technologies are actually limited by technical, financial, and social reasons. Second, the context of applying Smart PSS dynamically changes, which makes designed Smart PSS unfit to the target situation. To overcome these challenges, we propose an evolutionary design framework for Smart PSS. Our approach is based on the service engineering research, which has been contributing to the design and development of PSS. The proposed framework consists of three conceptual spaces and three cycles. The main features of the framework were two design cycles; in-system and ex-system design cycle. In-system design cycle is a process of creating and applying human knowledge for making the most use of data collected by digital technologies. Ex-system design cycle is to adapt to dynamic changes in contexts of the applied Smart PSS. We examine how the proposed framework works for designing a Smart PSS, with a case study about the digitalization of a restaurant business.     

A Middleware-Based Simulation and Control Framework for Mobile Service Robots

A mobile service robot is a complex distributed system integrating various technologies and having large heterogeneity. In order to facilitate component development and system integration of the mobile service robots, a middleware-based simulation and control framework for system integration and application development, as well as the robotic functional component (RFC) framework with a simplified structure and an efficient transmission scheme, is proposed for mobile service robot systems. Designed to implement a distributed modular mechanism for a mobile service robot, the middleware-based framework for simulation and control is comprised of four layers: low-level abstraction layer, communication layer, high-level abstraction layer, and application layer. Common Object Request Broker Architecture (CORBA) and Robot Technology Middleware (RTM) are employed as middleware for the development of RFCs and for system integration. Communication between the components and the graphical programming tool is done by the communication layer (CORBA ORB). The conducted experiments validated the proposed framework in terms of ideal performance of reusability, interoperability, and extensibility, as well as indicated that the proposed RFC framework is simplified and easy enough to perform well in data transmission, which will reduce the costs and the threshold of robot development.     

Skill Learning for Robotic Insertion Based on One-shot Demonstration and Reinforcement Learning

Machine Intelligence Research - In this paper, an efficient skill learning framework is proposed for robotic insertion, based on one-shot demonstration and reinforcement learning. First, the robot...     

Realization of task-based designs involving DH parameters: a modular approach

Task-based designs—proven to be successful for constrained environments—may face challenges at prototype development phase. To assist in generalized design and development of task-based serial manipulators for cluttered environments, a parameters-based modular approach is proposed. First, a task-based design strategy for serial manipulators is exhibited, using all the robotic parameters (DH parameters) as variables. The flexibility in robotic parameters enhances the possibility of good designs even for highly cluttered workspaces, but the realization of the resulting complicated designs is challenging. This work is an attempt to develop modular manipulators in correspondence to the task-based designs. The DH parameters-based proposed link modules, with reconfigurable architecture, can be adjusted and assembled to acquire the serial manipulators with designed robotic parameters. To validate the concept, some standardized 3R-configurations have been modelled using the proposed link modules. Case studies are presented on task-based design of robotic manipulators, with six and eight degrees of freedom, for service applications in realistic environments. The selected case studies include the robot design processes for applications of cleaning solar panels, and for the maintenance of the nuclear plants.     

PDE-based robust robotic navigation

In robotic navigation, path planning is aimed at getting the optimum collision-free path between a starting and target locations. The optimality criterion depends on the surrounding environment and the running conditions. In this paper, we propose a general, robust, and fast path planning framework for robotic navigation using level set methods. A level set speed function is proposed such that the minimum cost path between the starting and target locations in the environment, is the optimum planned path. The speed function is controlled by one parameter, which takes one of three possible values to generate either the safest, the shortest, or the hybrid planned path. The hybrid path is much safer than the shortest path, but less shorter than the safest one. The main idea of the proposed technique is to propagate a monotonic wave front with a particular speed function from a starting location until the target is reached and then extracts the optimum planned path between them by solving an ordinary differential equation (ODE) using an efficient numerical scheme. The framework supports both local and global planning for both 2D and 3D environments. The robustness of the proposed framework is demonstrated by correctly extracting planned paths of complex maps.     

服务机器人云平台服务质量指标体系综述

服务机器人的诞生丰富了人们的生活,并且随着大数据、云计算等技术的迅速发展,服务机器人连接云平台并从中调取算法服务已经能够实现,云服务机器人已然成为服务机器人的重点研究方向之一,而服务机器人云平台作为云服务机器人的云端服务平台有着重要的作用,需要对服务机器人云平台服务质量进行全面地评估,使服务机器人云平台能够和云服务机器人更好地结合。对服务机器人云平台服务质量指标体系进行综述,分别从软件QOS指标、网络QOS指标、服务机器人QOS指标三方面展开研究,并对三方面指标内容进行总结分析,得出一种服务机器人云平台服务质量指标体系,通过该体系能够对目前的服务机器人云平台以及相关云服务机器人的服务质量进行较为全面地评估,对该体系的未来发展进行展望。     

A dynamics formulation of general constrained robots

The complexity of a standard compact-in-form Lagrangian dynamical expression is proportional to the fourth power of the number of degrees of freedom (DOF) of a robotic system. This fact challenges both simulation and control of robots with hyper degrees of freedom. In this paper, a systematic approach for deriving the dynamical expression of so-called general constrained robots is proposed. This proposed approach has two main features. First, it uses the subsystem dynamics such as the dynamics of joints and rigid links to construct the dynamical expression of the entire robotic system in a closed form. The complexity of the resulted dynamic expression is linearly proportional to the number of DOF of a robotic system. Second, it extends the standard dynamical form and properties of the conventional single-arm constrained robots to a class of more general robotic systems including the coordinated multiple-arm robotic systems. Three spaces, namely the general joint space, the general task space, and the extended subsystems space, are connected through corresponding velocity/force mapping matrices.An erratum to this article can be found at     

User authentication and undeniable billing support for agent-based roaming service in WLAN/cellular integrated mobile networks

In this paper, a framework of authentication and undeniable billing support for an agent-based roaming service in WLAN/cellular networks interworking networks is proposed. This framework circumvents the requirement of peer-to-peer roaming agreements to provide seamless roaming service between WLAN hotspots and cellular networks operated by independent wireless network service providers. Within the framework, an adaptive authentication and an event-tracking scheme have been developed, which allow the application of undeniable billing service to cellular network even when it still uses a traditional authentication scheme. The proposed modified dual directional hash chain (MDDHC) based billing support mechanism features mutual non-repudiation. Security analysis and overhead evaluation demonstrate that the proposed framework is secure and efficient.     

面向智能家居/智慧生活的服务机器人技术与系统

随着机器人技术的发展以及服务机器人形态的日益丰富,智能家居/智慧生活逐渐成为一种未来的生活方式。文章探索了智能家居和智慧生活的服务机器人技术与系统,在其众多的关键技术中,重点探讨了面向服务机器人的云端融合技术以及高用户体验度的人-机器人交互技术。并以家庭服务机器人为例,实现了基于微信和语音云的人-机器人交互方式,验证了基于云架构的家庭服务机器人体系结构的可行性。文章所提出的服务机器人技术与系统是智能家居、智慧生活的一种实现方式,为未来形形色色的服务机器人技术方案提供了一些思路。     

Improving the Behavior of Intelligent Tutoring Agents with Data Mining

This article presents a novel framework for adapting the behavior of intelligent agents. The framework consists of an extended sequential pattern mining algorithm that, in combination with association rule discovery techniques, is used to extract temporal patterns and relationships from the behavior of human agents executing a procedural task. The proposed framework has been integrated within the CanadarmTutor, an intelligent tutoring agent aimed at helping students solve procedural problems that involve moving a robotic arm in a complex virtual environment. We present the results of an evaluation that demonstrates the benefits of this integration to agents acting in ill-defined domains.     

A vision-centered multi-sensor fusing approach to self-localization and obstacle perception for robotic cars

Most state-of-the-art robotic cars’ perception systems are quite different from the way a human driver understands traffic environments. First, humans assimilate information from the traffic scene mainly through visual perception, while the machine perception of traffic environments needs to fuse information from several different kinds of sensors to meet safety-critical requirements. Second, a robotic car requires nearly 100% correct perception results for its autonomous driving, while an experienced human driver works well with dynamic traffic environments, in which machine perception could easily produce noisy perception results. In this paper, we propose a vision-centered multi-sensor fusing framework for a traffic environment perception approach to autonomous driving, which fuses camera, LIDAR, and GIS information consistently via both geometrical and semantic constraints for efficient self-localization and obstacle perception. We also discuss robust machine vision algorithms that have been successfully integrated with the framework and address multiple levels of machine vision techniques, from collecting training data, efficiently processing sensor data, and extracting low-level features, to higher-level object and environment mapping. The proposed framework has been tested extensively in actual urban scenes with our self-developed robotic cars for eight years. The empirical results validate its robustness and efficiency.     

Passive Bilateral Teleoperation With Constant Time Delay

We propose a novel control framework for bilateral teleoperation of a pair of multi-degree-of-freedom nonlinear robotic systems under constant communication delays. The proposed framework uses the simple proportional-derivative control, i.e., the master and slave robots are directly connected via spring and damper over the delayed communication channels. Using the controller passivity concept, the Lyapunov–Krasovskii technique, and Parseval's identity, we can passify the combination of the delayed communication and control blocks altogether robustly, as long as the delays are finite constants and an upper bound for the round-trip delay is known. Having explicit position feedback through the delayed P-action, the proposed framework enforces master–slave position coordination, which is often compromised in the conventional scattering-based teleoperation. The proposed control framework provides humans with extended physiological proprioception, so that s/he can affect and sense the remote slave environments mainly relying on her/his musculoskeletal systems. Simulation and experiments are performed to validate and highlight properties of the proposed control framework.     

Flexible telemanipulation based handy robot teaching on tape masking with complex geometry

Traditional robot teaching methods are cumbersome, tedious and difficult to scale for high-mix low-volume applications. The tape masking, a common process for surface protection before plasma spraying, spray painting and shot peening, is one of those domains where robotic automation lacks flexibility and reliability due to the complexity in task. Fortunately, it is still within the grasps of human-robot collaborative systems. This work presents a telemanipulation-based robot teaching framework that is able to let the robot manipulator cope with the taping tasks with complex workpiece geometries. The proposed framework allows quick calibration, variable motion mapping, and indexing so that the operators can easily set up and guide the robotic taping system to cover the tapes onto the layers and grooves of different workpieces. This framework enables the operators to change the motion mapping scale for both large-scale guidance and fine motion dexterous manipulation. Meanwhile, an indexing function makes it possible for the operators to re-map their poses from the edges of their comfortable regions. A portable VR system is applied in the telemanipulation system. With its six DoF motion precisely measured in real-time, the proposed motion remapping algorithms enable the operators to directly guide the robot in their selected scales. Experimental results show that the proposed framework facilitates robot programming on the manipulation of the complex workpieces that have multi-layer surfaces and grooves in between. It also reduces the teaching time comparing to other methods. This system and method improve teaching efficiency and convenience, which has potential value to be deployed in manufacturing.     

Autonomous robotic capture of non-cooperative target using visual servoing and motion predictive control

This paper presents a framework for autonomous capture operation of a non-cooperative mobile target in a 3-dimensional workspace using a robotic manipulator with visual servoing. The visual servoing with an eye-in-hand configuration is based on motion predictive control using Kalman filter for the on-line state and parameter estimation of the target. A transitional decision making process is developed to guide the robotic manipulator between the different phases of the capture operation by employing a custom metric that translates visual misalignments between the end-effector and the target into a guidance measurement. These phases include the target acquisition and approach stage and the alignment and capture phase. Experiments have been carried out on a custom designed and built robotic manipulator with 6 degrees of freedom. The objective is to evaluate the performance of the proposed motion predictive control scheme for the autonomous capturing task and to demonstrate the robustness of the proposed control scheme in the presence of noise and unexpected disturbances in vision system, sensory-motor coordination and constraints for the execution in real environments. Experimental results of the visual servoing control scheme integrated with the motion predictive Kalman filter indicate the feasibility and applicability of the proposed control scheme. It shows that when the target motion is properly predicted, the tracking and capture performance has been improved significantly.