管道喷涂机器人:结构与位姿调整

针对工业上大型管道内壁喷涂的需求,设计了用于喷涂管道的机器人,该机器人采用串并联结构形式,由支撑平台和串联机械手组成.支撑平台采用几何的方法建立数学模型,串联机械手采用D-H参数法建模;并在数学模型基础上给出了逆解方程.位姿调整时,对机器人进行初定位,利用激光跟踪仪测量出管道和机器人的位姿,求解出调整量,对机器人进行位姿调整,使喷枪旋转轴和管道轴线重合.管道喷涂机器人在工厂进行试验测试,测试结果表明该装备可以很好地实现管道的喷涂,提高喷涂质量和效率.      

High-adaption locomotion with stable robot body for planetary exploration robot carrying potential instruments on unstructured terrain

There is a strong demand for Planetary Exploration Mobile robots (PEMRs) that have the capability of the traversability, stability, efficiency and high load while tackling the specialized tasks on planet surface. In this paper, an electric parallel wheel-legged hexapod robot which has high-adaption locomotion on the unstructured terrain is presented. Also, the hybrid control framework, which enables robot to stably carry the heavy loads as well as to traverse the uneven terrain by utilizing both legged and wheeled locomotion, is also proposed. Based on this framework, robot controls the multiple DOF leg for performing high-adaption locomotion to negotiate obstacles via Gait Generator (GG). Additionally, by using Whole-Body Control (WBC) of framework, robot has the capability of flexibly accommodating the uneven terrain by Attitude Control (AC) kinematically adjusting the length of legs like an active suspension system, and by Force/torque Balance Control (FBC) equally distributing the Ground Reaction Force (GRF) to maintain a stable body. The simulation and experiment are employed to validate the proposed framework with the physical system in the planetary analog environments. Particularly, to smoothly demonstrate the performance of robot transporting heavy loads, the experiment of carrying 3-person load of about 240 kg is deployed.     

Towards intelligent design optimization: Progress and challenge of design optimization theories and technologies for plastic forming

Plastic forming is one of enabling and fundamental technologies in advanced manufacturing chains. Design optimization is a critical way to improve the performance of the forming system, exploit the advantages of high productivity, high product quality, low production cost and short time to market and develop precise, accurate, green, and intelligent (smart) plastic forming technology. However, plastic forming is quite complicated, relating to multi-physics field coupling, multi-factor influence, multi-defect constraint, and triple nonlinear, etc., and the design optimization for plastic forming involves multi-objective, multi-parameter, multi-constraint, nonlinear, high-dimensionality, non-continuity, time-varying, and uncertainty, etc. Therefore, how to achieve accurate and efficient design optimization of products, equipment, tools/dies, and processing as well as materials characterization has always been the research frontier and focus in the field of engineering and manufacturing. In recent years, with the rapid development of computing science, data science and internet of things (IoT), the theories and technologies of design optimization have attracted more and more attention, and developed rapidly in forming process. Accordingly, this paper first introduced the framework of design optimization for plastic forming. Then, focusing on the key problems of design optimization, such as numerical model and optimization algorithm, this paper summarized the research progress on the development and application of the theories and technologies about design optimization in forming process, including deterministic and uncertain optimization. Moreover, the applicability of various modeling methods and optimization algorithms was elaborated in solving the design optimization problems of plastic forming. Finally, considering the development trends of forming technology, this paper discusses some challenges of design optimization that may need to be solved and faced in forming process.     

辐射开环空间绳系机器人编队动力学及控制

提出了一种新型辐射开环空间绳系机器人编队系统,其在编队稳定性、任务灵活性及燃料消耗等方面具有明显的优势。针对辐射开环空间绳系机器人编队系统自旋运动过程中的构型误差控制问题,首先建立了编队系统的自旋动力学模型;然后分析了空间绳系机器人的绳系拉力和空间平台的自旋扭矩对编队系统自旋运动中出现的构型误差的控制能力;设计了一种依靠空间绳系机器人绳系拉力和空间平台自旋扭矩作为控制量,对构型误差进行控制的协调控制方法;最后通过数字仿真进行了校验和分析。仿真结果表明：设计的协调控制方法能够明显改善编队系统自旋运动中构型误差的控制效果。     

星球巡视器任务规划技术发展综述

首先阐述了星球巡视器任务规划的定义、内容和特点,并分别从任务规划算法、全局路径规划算法、局部路径规划算法三个层面对国内外星球巡视器任务规划技术的研究现状进行了分析和评述。在任务规划层面,当前研究主要集中在基于资源调度的方法和基于路径的方法;在全局路径规划层面,介绍了路径图法、单元分解法等几何模型构建算法以及A*类算法等图搜索算法;在局部路径规划层面,介绍了人工势场法、Bug类算法、启发式动态重规划算法、基于地形评估的算法等几类常用算法。最后,对星球巡视器任务规划技术的未来发展方向进行了展望。     

壁面吊挂清洗机器人碰壁缓冲问题研究

从机器人自动上壁及缓冲的需求出发,分析了机器人拉力形成的机理、碰壁的原因和过程.利用空气动力学原理,给出了拉力的计算方法,采用机器人物理样机进行实验,对计算结果进行了验证.在拉力的作用下机器人与壁面贴合,同时伴随碰撞,其间冲击能量的吸收由机器人裙边和支撑机构所构成的缓冲装置承担.前者还要保证机器人贴壁后的密封,因此刚度不宜过大,后者还要保证机器人在壁面上稳定行走,因此它的刚度又不宜过小.给出了缓冲装置刚度的确定方法及其在裙边和支撑机构上的分配准则,可用于工程分析.     

一种基于遗传RBF神经网络的智能容错滤波算法

针对组合导航中标准卡尔曼滤波容错性能不足的问题,提出一种基于遗传RBF神经网络的智能容错滤波算法,其基本思想是通过RBF网络自动调节滤波增益来控制不确定性噪声的影响,进而提高滤波容错性。在RBF神经网络中,隐层单元与核函数宽度的选取对网络的性能具有重要影响,进而利用自适应遗传算法对其隐层单元数及核函数宽度进行了优化,隐层单元中心和输出层连接权值分别由K-均值聚类和最小二乘算法确定,最后得到精度较高且结构优化的RBF网络。为检验方法的应用效果,以SINS/GPS组合导航系统为例进行了仿真验证,实验结果表明遗传RBF网络容错滤波算法能在满足导航精度和计算量增加较小的前提下,比标准卡尔曼滤波具有更强的容错能力,由此也说明了方法的有效性。     

空间机械臂位形与基座姿态协同控制研究

针对自由飘浮空间机械臂与基座的运动耦合问题,提出了一种基于不变流形的机械臂位形与基座姿态协同控制算法。在分析了系统可控性的基础上,构造了线性状态反馈下系统的不变流形,并设计了分段连续的镇定控制器。该控制器先将系统状态镇定到不变流形之上,然后沿该流形将系统状态调整到期望值。仿真结果表明,在系统可控的条件下,所提出的协同控制算法能将机械臂位形与基座姿态同时调整到期望状态。     

基于多项式插值的自由漂浮空间机器人轨迹规划粒子群优化算法

针对自由漂浮空间机器人轨迹规划问题,提出一种基于多项式插值与粒子群优化算法相结合的非完整运动规划方法。首先,通过对系统非完整约束条件进行分析,给出了以机械臂关节角耗散能为目标函数的轨迹最优控制算法;并采用高阶多项式插值方法逼近机械臂关节角轨迹,将插值多项式的系数作为优化参数,结合粒子群优化算法对关节角轨迹进行优化求解。最后,对本文提出的轨迹规划算法进行数值仿真。仿真结果表明关节角轨迹平滑连续,保证了关节角速度及关节角加速度在初始和终止状态均为零,从而验证了所提方法的有效性和可行性。