关键词： 参数辨识   基于模型的前馈控制   人工蜂群算法   非线性摩擦模型  

摘要： 实验辨识机器人动力学参数是获取基于模型的控制器参数的主要方式。针对一般方法仅能辨识线性动力学模型从而辨识精度不高的问题,提出采用人工蜂群(Artificial bee colony,ABC)算法辨识机器人动力学模型。通过Newton-Euler法建立关节型机器人的刚体动力学模型,并用低速动态特性更佳的非线性摩擦模型描述关节间摩擦特性,代替传统的库仑-黏性摩擦模型。优化辨识实验所用的激励轨迹,采集实验数据进行必要的预处理后,采用ABC算法辨识机器人动力学参数。结果表明,ABC算法能够精确辨识动力学参数,基于辨识结果的预测力矩抑制了误差峰值的出现。应用辨识结果设计基于模型的前馈控制器,实验结果表明基于模型的控制器能够提高轨迹跟踪精度。

关键词： SCARA机器人   动力学参数辨识   牛顿欧拉方法   关节力矩  

摘要： SCARA机器人在工业生产中得到了广泛应用.为满足高速、高精度的要求,必须对SCARA机器人进行动力学分析.文中用牛顿欧拉方法对SCARA机器人进行动力学建模,并将摩擦力以及电机转子对关节力矩的影响纳入动力学模型,得出了关节力矩关于一组可辨识参数集的线性表达式.采用傅里叶级数作为激励轨迹进行实验,并通过最小二乘法对得出的可辨识动力学参数集进行辨识.实验证明,通过推导的线性表达式计算出的关节力矩理论值与实际值的变化趋势一致.运用所提方法辨识的动力学参数进行动力学建模,能得到SCARA机器人运动时的关节力矩,可为后期的动力学控制提供基础计算公式.

关键词： 管道清洁机器人   撑开机构   ADAMS   动力学   仿真  

摘要： 建立了管道清洁机器人的三维本体结构模型,针对机器人在变径管、弯管、T型管内运动干涉问题,提出了一种新型撑开机构,建立了撑开机构的机构运动简图;利用牛顿欧拉法建立机器人撑开机构的动力学方程并求解;用ADAMS软件建立了撑开机构动力学仿真模型,并进行了动力学仿真分析。仿真结果表明,机器人撑开机构滑块速度方向改变时,机构各杆件受力达到最大。

关键词： 机器人   学院   佛山   HARTING   MICA   制造业   开幕式   展览会  

摘要： 浩亭作为工业4.0的先锋,誓为中国智能制造业发展做出贡献,积极参与成为佛山机器人学院的创始成员。开幕式定于10月12日,与第三届“互联网＋”展览会开幕典礼同时进行。浩亭将于机器人学院展示HARTING MICA（模块化工业计算架构）。MICA提供迅捷简便的解决方案,直接在设施和机器上实现数字化项目。

关键词： 多传感器融合   递推总体最小二乘   水下机器人   参数辨识  

摘要： 对于水下机器人动力学模型辨识问题,如果其观测方程的系数矩阵包含随机扰动,则其最小二乘估计一般是有偏的。为此,该文提出一种基于多传感器递推总体最小二乘融合的水下机器人动力学模型辨识算法(RTLS_F)。首先,给出了集中式总体最小二乘融合的算法;然后,在总体最小二乘框架下,推导出多传感器递推融合估计算法。通过仿真实验对RTLS_F与其它水下机器人动力学参数辨识算法进行了比较。实验结果表明,在系数矩阵和观测向量都含有误差的情况下,最小二乘融合是有偏估计且难以提高估计精度,而RTLS_F算法可以有效改善参数辨识性能。

关键词： 机器人学   人工智能   人类智能   机会损失   副总裁   卡尔森   专家预言   未来   特种机器人   用工人数  

摘要： 曾经有专家预言,未来十年,人类一半以上的职业将被人工智能所取代。我们是应该拥抱它,还是心生恐惧？在2017成都全球创新创业交易会人工智能/机器人峰会上,来自美国的专家们带来了前瞻性的分享。美国创业平台公司研究副总裁及首席科学家尼克拉斯·卡尔森认为,技术的应用并不会造成大量就业机会的损失。他举例说,他有一位朋友为酒店做机器人,但是员工并没有被机器人取代,反而倒逼了员工提高工作效率,为企业创造更大的利润。因此他肯定地说：＂机器人和人工智能适合做任务,并不是取代了人类智能。＂

关键词： Cloud robotics   Energy consumption   Green software modeling method   State transition matrix   Bounded model checking  

摘要： The energy consumption of cloud robotics is an important design factor to be considered early in system development. Software as the main enabler of cloud robots, its energy consumption will directly influence the energy consumption level of the entire system. In this paper, we propose a green software model for cloud robotics based on energy consumption time state transition matrix (ETSTM), which can effectively integrate the logic functions, energy consumption, and execution time of software into a single model. To improve the practicability of ETSTM, we provide a software energy consumption function based on software characteristic fitting by a backpropagation (BP) neural network, which can be used to predict software energy consumption. Furthermore, we provide two types of energy consumption analysis algorithms based on explicit execution path search and bounded model checking (BMC) for ETSTM. The experiment results show that the proposed method can achieve good performance. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Autonomous Driving Competition   Educational Robotics   Gazebo   Hardware in-the-loop Simulation   Mobile Robotics   ROS - Robotics Operating System   STEM - Science Technology Engineering Mathematics  

摘要： Interest in robotics field as a teaching tool to promote the STEM areas has grown in the past years. The search for solutions to promote robotics is a major challenge and the use of real robots always increases costs. An alternative is the use of a simulator. The construction of a simulator related with the Portuguese Autonomous Driving Competition using Gazebo as 3D simulator and ROS as a middleware connection to promote, attract, and enthusiasm university students to the mobile robotics challenges is presented. It is intended to take advantage of a competitive mindset to overcome some obstacles that appear to students when designing a real system. The proposed simulator focus on the autonomous driving competition task, such as semaphore recognition, localization, and motion control. An evaluation of the simulator is also performed, leading to an absolute error of 5.11% and a relative error of 2.76% on best case scenarios relating to the odometry tests, an accuracy of 99.37% regarding to the semaphore recognition tests, and an average error of 1.8 pixels for the FOV tests performed.

关键词： Assistive and rehabilitation robotics   Human-oriented approaches   Physical and cognitive capabilities   Assessment   Design methods   Wearable robotics  

关键词： Disaster robot   Mobility   Manipulability   Human-robot interface   Autonomy  

摘要： As we witnessed in recent major disasters, the functionalities of robots in disaster environments do not appear to meet the high level of expectation from the public. This paper reviews robotic operations in disaster situations and open issues with the current robotic technologies. We particularly address fundamental problems with teleoperated ground robots for disaster response and recovery: design of robot platforms and balance between human supervisory control and robotic anatomy. In attempt to alleviate the problems, this paper suggests enabling technologies to improve the effectiveness of robotic systems for disaster response and recovery missions.