工业机器人虚拟样机系统的研究

该文提出将虚拟样机技术应用于工业机器人仿真研究过程,研究与开发工业机器人虚拟样机系统,首先说明虚拟样机技术并分析其关键技术,然后说明了工业机器人虚拟样机系统的构成与样机系统在机器人仿具研究中的研究内容,总结该项技术主要解决以下两方面的问题,即机器人仿真研究中的系统集成及为以机器人为主体的生产线虚拟设计,验证环境提供底层的数字化环境。     

Time-constrained project scheduling with adjacent resources

We develop a decomposition method for the Time-Constrained Project Scheduling Problem (TCPSP) with adjacent resources. For adjacent resources the resource units are ordered and the units assigned to a job have to be adjacent. On top of that, adjacent resources are not required by single jobs, but by job groups. As soon as a job of such a group starts, the adjacent resource units are occupied, and they are not released before all jobs of that group are completed. The developed decomposition method separates the adjacent resource assignment from the rest of the scheduling problem. Test results demonstrate the applicability of the decomposition method. The presented decomposition forms a first promising approach for the TCPSP with adjacent resources and may form a good basis to develop more elaborated methods.     

Transformative CAD based industrial robot program generation

Industrial robots are widely used in various processes of surface manufacturing, such as spray painting, spray forming, rapid tooling, spray coating, and polishing. Robot programming for these applications is still time consuming and costly. Typical teaching methods are not cost effective and efficient. There are many off-line programming methods developed to reduce the robot programming effort. However, these methods suffer many practical issues, such as cable/hose tangling, robot configuration, collision, and reachability. To solve these problems, this paper discusses a new method to generate robot programs. Since industrial robots have been used in production for decades, there are many robot programs for different parts generated by the robot programmers. These robot programs, which contain not only the robot paths, but also the programmers' knowledge and process parameters, can be transformed to generate new robot programs for similar parts. In this paper, a transformative robot program generation method is developed based on the existing ones in the database. Experiments were performed to validate the developed methodology. The results are very promising in reducing the programming efforts in surface manufacturing.     

Development of a decision support system for robot selection

With the availability of more different robot types and models along with their separate specifications, selecting the most appropriate robot is becoming more difficult and complicated for companies. Furthermore, a common set of robot selection criteria is not available for the decision makers. In this study, a two-phase robot selection decision support system, namely ROBSEL, is developed to help the decision makers in their robot selection decisions. In development of ROBSEL, an independent set of criteria is obtained first and arranged in the Fuzzy Analytical Hierarchy Process (FAHP) decision hierarchy. In the first elimination phase of the decision support system, the user obtains the feasible set of robots by providing limited values for the 15 requirements. ROBSEL, then, uses FAHP decision hierarchy to rank the feasible robots in the second phase. ROBSEL is illustrated and tested and several critical issues in its practical usage are explored in the paper. The applications of ROBSEL show that ROBSEL is a useful, practical and easy to use robot selection tool and improves robot selection decisions in the companies.     

Team RuBot’s experiences and lessons from the ARIAC

We share experiences and lessons learned in participating the annual Agile Robotics for Industrial Automation Competition (ARIAC). ARIAC is a simulation-based competition focusing on pushing the agility of robotic systems for handling industrial pick-and-place challenges. Team RuBot started competing from 2019, placing 2nd place in ARIAC 2019 and 3rd place in ARIAC 2020. The article also discusses the difficulties we faced during the contest and our strategies for tackling them.Video of system sketches: https://youtu.be/7H7YLeJz2zE.     

关节驱动系统非线性摩擦最小能耗分析

节能降耗是现代工业生产的普遍需要。针对直流电机和减速齿轮驱动下的机械臂关节,详细论述了非线性摩擦最小能耗的分析和计算方法。在PTP位置控制系统中,耗散能量的最小化取决于最佳穿越时间。仿真和实验的结果证明了这一结论。     

Resource-efficient routing and scheduling of time-constrained streaming communication on networks-on-chip

Network-on-chip-based multiprocessor systems-on-chip are considered as future embedded systems platforms. One of the steps in mapping an application onto such a parallel platform involves scheduling the communication on the network-on-chip. This paper presents different scheduling strategies that minimize resource usage by exploiting all scheduling freedom offered by networks-on-chip. It also introduces a technique to take the dynamism in applications into account when scheduling the communication of an application on the network-on-chip while minimizing the resource usage. Our experiments show that resource-utilization is improved when compared to existing techniques.     

基于ROS的机器人自动手眼标定系统设计

为了缩短标定的时间,设计了一种基于ROS的机器人自动手眼标定系统。通过分析坐标系间的转换关系,建立了手眼标定的数学模型,推导了两步法的具体解法。为了尽可能减小标定误差,提出了带约束的随机增量法,并根据角点检测结果实时剔除标定过程中出现的无效图像。基于ROS软件平台完成了驱动、运动空间规划、图像处理和标定解算等功能模块的逻辑设计和系统级联。以6自由度工业机械臂UR3和RGB-D相机Kinect2构建了手眼标定实验系统,实验结果表明,与传统标定流程相比,所设计的自动手眼标定系统便捷高效且精度高,具有较强的拓展性。     

Adaptive robot training by programming and guiding

The simplest and most common robot training method is operator-guiding, but this method is inflexible and limited to fixed sequences. Explicit textual robot programming has enjoyed many advances in the last decade and current research implementations are powerful. But explicit programming is complex and programmers must be specially trained. Mixed systems attempt to unite the facility of guiding with the power of programming. However, existing mixed systems exhibit mismatches in the interaction between programming and guiding, because they ignore underlying dependencies between the programmer and operator. An operator may (1) be given insufficient visual cues; (2) lack the required dexterity; or (3) be required to add unforeseen movement sequences to the program. This paper presents the design and implementation of ART (adaptive robot trainer), a prototypical mixed robot training system that eliminates or corrects deficiencies in visual cues and dexterity, and additionally improves the guiding and programming components. Mixed systems and assembly tasks are analysed, to give an effective representation of task state, which in turn motivates the design of ART's language to automate much of the program-guiding interaction. The language allows the programmer to express assembly operations and object-feature relationships in a natural way while providing the system with the information necessary to maintain the task state. The representation also enables the correction of guiding errors, flexibility in the guiding protocol and the generation of meaningful messages to prompt operator actions. These principles in the design and implementation pave the road to more instructable, capable robots.Now at Bell Northern Research, Ottawa.     

GPU/CPU异构系统任务节能调度方法仿真

研究GPU/CPU异构系统任务调度的节能问题.与传统同构体系结构相比,异构系统任务调度呈现较大的随机性和不定性,GPU/CPU异构系统中时间间隙片段呈现了较大的随机性,导致传统调度方法很难建立规则的描述时间片段的模型,调度能耗较高.为解决上述问题,提出了一种改进功耗优化的GPU/CPU异构环境下的任务调度算法,将任务关系图按照依赖关系计算量拆分,并分配到计算节点.在计算节点内根据权重法的思想,统计所有计算节点的处理情况,进而将节点内的子任务调度到合适的处理器.实验结果表明,在不影响应用性能的前提下,降低了异构系统的能耗开销,优化效果明显.     

云计算环境下的节能任务调度策略的随机Petri网分析

针对当前云计算异构服务器集群环境下的高能耗问题,提出一种最小能耗优先的任务调度策略(first sche-duling with minimum energy)。该策略在调度任务时优先考虑处于运行状态的服务器,并以任务响应时间为约束,按照最小能耗原则将任务分配到相应的服务器上执行。当处于运行状态的服务器都不能满足任务对响应时间的要求时,则考虑处于休眠状态的服务器;同时,也基于最小能耗原则进行调度。采用随机Petri网工具对节能任务调度策略进行分析建模,考虑其能耗和相关性能指标。实验结果表明,该方法不仅能满足任务的QoS性能要求,而且具有较好的节能效果。     

开放式机器人通用控制系统

将数字信号处理器(DSP)为核心的多轴运动控制技术运用于机器人控制,本文提出了一种新的开放式结构机器人通用控制系统．文中阐述了系统的硬、软件结构,并对系统中主要功能模块的技术细节进行了分析．最后给出了本系统的部分实验结果．     

Cyclic routing algorithms in graphs: Performance analysis and applications to robot scheduling

In this paper we revisit and extend the algorithm for the cyclic project scheduling problem which was originally proposed by Romanovskii (1967). While the algorithm has been derived for fixed numerical data, we show how it can be extended to handle the problems with interval data. We also propose a new algorithm for the cyclic scheduling problem with interval data that extends the parametric method developed by Megiddo (1979) and runs in strongly polynomial time.     

一个开放式移动机器人体系结构

本文首先说明了体系结构研究的内容，研究体系结构的意义，以及当前几个典型体系结构研究范例，然后较详细地介绍了开放式体系结构ＯＳＭＯＲ及其在传感器处理方面的特点，并分别讨论了结构中各模块的功能及实现方法。     

改进灰狼优化算法求解机器人作业车间调度问题

针对物料机器人指派和作业车间的联合调度问题,设计了一种改进灰狼优化算法进行求解。根据机器人作业车间调度和灰狼优化算法的各自特点,提出一种面向机器人转移工序的编码方式。解码时,考虑工件运输的前提是工件在当前机器的工序已加工,提出融合间隙解码方法的驱动解码方法。为避免算法陷入局部最优,在灰狼个体位置更新后加入个体变异方法。最后,通过与其他智能优化算法及同类算法进行比较,验证了所提灰狼优化算法的有效性。     

网络机器人实时监控系统的仿真研究

在基于网络的机器人远程控制系统研究中,大量视频图像数据在网络的传输导致的延时很难保证控制者能够实时监控机器人的状态。该文从仿真的角度提出了一种有效的方案,通过减少传输数据的方式减小延时。文章对机器人的几何建模和运动建模进行了研究,然后在VC＋＋6．0语言平台下,借助CAD软件SolidWorks,运用OpenGL完成了机器人的建模和三维显示;仿真系统通过网络实时的获取机器人的位置和姿态参数,动态地以三维模拟的方式显示,使得远程用户可以实时地监控机器人的运动状态,以采取适当的控制措施。     

Applied ontologies and standards for service robots

Service robotics is an emerging application area for human-centered technologies. The rise of household and personal assistance robots forecasts a human–robot collaborative society. One of the robotics community’s major task is to streamline development trends, work on the harmonization of taxonomies and ontologies, along with the standardization of terms, interfaces and technologies. It is important to keep the scientific progress and public understanding synchronous, through efficient outreach and education. These efforts support the collaboration among research groups, and lead to widely accepted standards, beneficial for both manufacturers and users. This article describes the necessity of developing robotics ontologies and standards focusing on the past and current research efforts. In addition, the paper proposes a roadmap for service robotics ontology development. The IEEE Robotics & Automation Society is sponsoring the working group Ontologies for Robotics and Automation. The efforts of the Working group are presented here, aiming to connect the cutting edge technology with the users of these services—the general public.     

Robot introspection through learned hidden Markov models

In this paper we describe a machine learning approach for acquiring a model of a robot behaviour from raw sensor data. We are interested in automating the acquisition of behavioural models to provide a robot with an introspective capability. We assume that the behaviour of a robot in achieving a task can be modelled as a finite stochastic state transition system.Beginning with data recorded by a robot in the execution of a task, we use unsupervised learning techniques to estimate a hidden Markov model (HMM) that can be used both for predicting and explaining the behaviour of the robot in subsequent executions of the task. We demonstrate that it is feasible to automate the entire process of learning a high quality HMM from the data recorded by the robot during execution of its task.The learned HMM can be used both for monitoring and controlling the behaviour of the robot. The ultimate purpose of our work is to learn models for the full set of tasks associated with a given problem domain, and to integrate these models with a generative task planner. We want to show that these models can be used successfully in controlling the execution of a plan. However, this paper does not develop the planning and control aspects of our work, focussing instead on the learning methodology and the evaluation of a learned model. The essential property of the models we seek to construct is that the most probable trajectory through a model, given the observations made by the robot, accurately diagnoses, or explains, the behaviour that the robot actually performed when making these observations. In the work reported here we consider a navigation task. We explain the learning process, the experimental setup and the structure of the resulting learned behavioural models. We then evaluate the extent to which explanations proposed by the learned models accord with a human observer's interpretation of the behaviour exhibited by the robot in its execution of the task.