关键词： Deep Reinforcement Learning (DRL)   Proximal Policy Optimisation (PPO)   Grad-CAM analysis   Domain randomisation   Robot welding  

摘要： Manufacturing companies are in constant need for improved agility. An adequate combination of speed, responsiveness, and business agility to cope with fluctuating raw material costs is essential for today's increasingly demanding markets. Agility in robots is key in operations requiring on-demand control of a robot's tool position and orientation, reducing or eliminating extra programming efforts. Vision-based perception using full-state or partial-state observations and learning techniques are useful to create truly adaptive industrial robots. We propose using a Deep Reinforcement Learning (DRL) approach to solve path-following tasks using a simplified virtual environment with domain randomisation to provide the agent with enough exploration and observation variability during the training to generate useful policies to be transferred to an industrial robot. We validated our approach using a KUKA KR16HW robot equipped with a Fronius GMAW welding machine. The path was manually drawn on two workpieces so the robot was able to perceive, learn and follow it during welding experiments. It was also found that small processing times due to motion prediction (3.5 ms) did not slow down the process, which resulted in smooth robot operations. The novel approach can be implemented onto different industrial robots to carry out different tasks requiring material deposition.

关键词： Dynamic analysis   Monte Carlo method   Multi-robot system   Towing system   Workspace  

摘要： A multi-robot collaborative towing system fixed on floating base for high load marine work was established in this paper, and its dynamics and workspace were analyzed. An improved Monte-Carlo method was optimized, considering that this method cannot be directly used for the multi-robot system. Firstly, according to the structure of the system, the dynamics equations of the towing mechanism and the floating base were established by using the Newton-Euler method and rigid body dynamics, respectively. Then, an improved Monte-Carlo method was optimized, and the specific steps of solving the dynamic workspace by the optimized method were provided. Lastly, the system was divided into three types according to the actuator, and their dynamic workspace were simulated with a practical example by the traditional Monte-Carlo method and the optimized method. The simulation results show that, compared with traditional method, the optimized method has higher efficiency and can figure a workspace with clear boundary. Results of this study lay a basis for the subsequent trajectory plan and stability analysis of the system.

关键词： Kalman filters  

摘要： Due to its widespread application in the robotics field, the Kalman filter has received increased attention from researchers. This work reviews some of the modifications conducted on to this algorithm over the last years. Problems such as the consistency, convergence, and accuracy of the filter are also dealt with. Sixty years after its creation, the Kalman filter is still used in autonomous navigation processes, robot control, and trajectory tracking, among other activities. The filter is not only restricted to robotics but is also present in different fields, such as economics and medicine. In addition, the characteristics of each modification on this filter are analyzed and compared.

关键词： 包装生产线   搬运   机器人   动力学   ADAMS  

摘要： 目的为了解决六轴机器人包装行业中装箱、搬运等工序的应用问题,主要基于包装生产线的搬运工序设计作业机器人并对其动力学进行研究。方法根据包装生产线搬运工序的作业特点,将机器人结构设计为六轴关节型机器人,每个关节均通过伺服电机连接减速器驱动,通过牛顿-欧拉法对机器人进行动力学分析,建立机器人模型,并运用ADAMS软件对其动力学进行仿真分析。结果所设计机器人关节的运动轨迹曲线平稳变化,轨迹平滑连续,角速度和角加速度曲线平滑、无突变。结论机器人运动平稳,在运动过程中振动较小,证明了结构设计的合理性,为六轴机器人的优化设计提供了理论基础。

关键词： SCARA机器人   动力学   参数辨识   随机权重   粒子群算法  

摘要： 针对SCARA机器人在负载条件下末端动力学参数难以辨识的问题,在分析负载对各关节力矩影响的基础上,对SCARA机器人进行了结构简化,利用Lagrange法建立带负载机器人的动力学数学模型,确定了需要辨识的机器人末端动力学参数。在传统粒子群算法的基础上,提出一种随机权重粒子群算法对机器人动力学参数进行辨识,并编写了相应的程序。仿真辨识结果表明:随机权重粒子群算法的收敛速度与参数粒子搜索范围得到明显提升,辨识出的机器人力矩与实际输出力矩基本吻合,说明该算法对机器人动力学参数的辨识具有较高的精度;与遗传算法、基本粒子群算法相比,随机权重粒子群算法辨识得到的适应度函数最优值最小,不易陷入局部最优,便于全局搜索,参数辨识精确更高。

关键词： 机器人竞赛   主题教育活动   科技创新教育   中洲   示范基地   岳阳市   岳阳县   演说家  

摘要： 湖南省岳阳县中洲乡兴旺学校(下文简称“学校”)科技活动蓬勃开展,学校荣获2020年全国青少年航空航天模型线上主题教育活动湖南站优秀组织奖,被岳阳市教体局评为“青少年科技活动示范基地”“岳阳市十佳科技创新教育学校”。从2017年起,学校学生参加岳阳市模型竞赛,共取得了3个一等奖、5个二等奖、4个三等奖的好成绩。学生周佳欣参加全国海洋演说家活动获二等奖,学生钱宇轩参加全国小盖茨机器人竞赛活动获优秀创意奖,学生钱宇轩、周婷婷、吴紫妍制作的科学DV获岳阳市二等奖。

关键词： Motors   Engines   Nonlinear dynamics   Modeling   Rotation  

摘要： In order to improve the accuracy of the robot dynamics model, a low-speed motion nonlinear dynamics modeling method of industrial robot based on phase space reconstruction neural network is proposed. It is confirmed in advance by the largest Lyapunov exponent of joint motor torque data that the robot has chaotic characteristics at low-speed motion. Therefore, experimental data and chaos theory is used to analyze low-speed motion nonlinear dynamics, instead of considering each factor that may cause the robot's nonlinear dynamics separately. The phase space reconstruction parameters of each joint are determined by autocorrelation method and false nearest neighbor method. Through data preprocessing and analysis, some joint position derivatives related to the changing law of torque data are determined. The phase space reconstruction values of these derivatives are chosen as the inputs of neural network. Then the neural network and curve fitting method are combined to compensate for the nonlinear joint torque. Experimental results show that the proposed method can better describe the robot's low-speed motion nonlinear dynamics, and has smaller errors compared with ordinary back propagation (BP) neural network in the case of single joint rotation.

关键词： 水下机器人   水动力系数   格子波尔兹曼方法   大振幅平面运动机构试验  

摘要： 为实现开架式水下机器人的操纵性预报和开展控制算法的研究,提出一种基于格子波尔兹曼方法(LBM)的水动力系数数值计算方法。对比LBM和传统雷诺平均Navier-Stokes方程方法在稳态纵荡运动和斜航运动中的模拟结果,验证LBM的可行性。建立大振幅非稳态平面运动机构试验的严格运动函数,根据水下机器人结构特点构建包含惯性水动力系数、线性与非线性黏性水动力系数的水动力模型,并采用最小二乘法辨识水动力模型参数。对标准操纵性试验进行数值仿真,验证所建立的6自由度运动方程的有效性。结果表明:与基于传统计算流体力学技术的水动力计算方法相比,LBM不会受水下机器人外形复杂程度的限制,避免了非稳态运动模拟中复杂动网格的更新难题;通过大振幅平面运动机构试验模拟缩短了水动力系数计算周期,该水动力学模型较完整,更适用于操纵性预报和控制算法的研究。

关键词： RV减速器   三维数字化模型   动力学分析   工业机器人  

摘要： 以UG NX软件为平台建立RV减速器结构三维数字化模型,研究RV减速器可视化设计方法和虚拟装配;应用机械系统动力学仿真软件ADAMS对虚拟样机模型进行运动学和动力学分析,得到RV减速器的各级转速、齿轮啮合力等参数,并分别进行分析.仿真结果表明:实验参数与理论计算值相吻合,验证了虚拟样机技术在RV减速器设计中的正确性,对提高RV减速器设计的速度和质量具有参考价值.

关键词： 搬运机器人   颜色分类   物料搬运  

摘要： 为解决物料物件分拣和堆垛搬运效率低下、任务繁重等问题,设计了一个智能分拣搬运机器人,其使用4个带编码器的直流电机、3个舵机、1个Arduino2560控制板、直流电机驱动板和稳压板,模拟工业自动化过程中自动化物流系统的作业过程。从起点开始,在比赛场地进行运动,把颜色不同但大小一致的物料进行归类,搬运至比赛设定目标区,完成后回到起点位置。机器人前方抓取采用套筒和钩子结合方式,套筒依靠后面齿轮啮合机构实现开合,齿轮由9 g小舵机为动力,可以完成物块快速抓取、准确摆放等任务。颜色识别模块选用GY-33模块,搭载TCS4725RGB芯片,采用IIC通信模式读取物块的RGB值,通过程序对RGB值进行比较,确认物块颜色。此结构设计打破传统结构设计方式,结构更加合理、稳定,满足了搬运工作的快速性、准确性要求。