柔性冗余度机器人力矩优化的研究

本文首先应用模态理论，对柔性冗余度机器人振动的控制问题的原理与策略进行了研究．在此基础上通过对满足抑振要求的自运动的选取进行分析，指出柔性冗余度机器人在通过优化其自运动实现振动抑制的同时还具有二次优化的能力，并给出了在满足抑振的前提下实现关节力矩优化的方法．最后对一个末杆为柔杆的平面三杆机械手的振动控制与力矩优化进行了仿真，结果验证了该方法的可行性．     

基于PSO非均匀样条插值的混合结构柔性臂抑振轨迹规划

柔性臂广泛应用于核工业、建筑业、太空探索等领域,但由于自身刚度低、大挠度、低阻尼等特点,其末端易产生振动且难以在短时间内消除.对此,研究一种具有一个旋转关节和一个伸缩关节的混合结构柔性臂的抑振轨迹规划方法.通过对其结构分解和刚柔部分分解,建立动力学和运动学模型.为了提高算法效率,引入权重因子,构造映射函数,选取非均匀插值点,采用粒子群算法(PSO)优化插值点位置增量,利用3次样条插值拟合优化后的轨迹函数.最后,通过设计混合柔性臂的控制系统,验证所提出抑振轨迹规划方法的有效性.     

柔性关节机器人抓取末端振动自动化控制方法

为了提高柔性关节机器人抓取末端振动控制精度,该文提出柔性关节机器人抓取末端振动自动化控制方法。对柔性关节机器人展开系统动力学分析,构建奇异摄动模型定义柔性关节机器人系统的运动方程。设计柔性关节机器人的优化控制器,构建控制误差代价函数。利用拉格朗日法获取函数最优解,实现柔性关节机器人抓取末端振动自动化控制。实验结果表明,该方法能够有效抑制柔性关节机器人末端振动信号,相位控制误差均在0.02°以内,抑振措施的上升时间低于7.66 s,末端控制精准度高、效率高、性能好。     

基于嵌入式系统的机器人关节空间轨迹规划

针对工业机器人运行过程经常出现的因速度或加速度不连续从而导致抖动等问题,提出了一种基于B样条曲线的轨迹规划算法,该算法使用三次B样条曲线来对六自由度机器人的关节空间进行插值,并根据实时性的要求运用一种控制点衔接插补算法进行分段插补,最终应用于基于ARM9的嵌入式系统中。实验证明:该算法不仅计算量小、处理时间短,而且能保证速度曲线的连续平滑,减少了机械抖动。     

基于混合遗传算法的工业机器人最优轨迹规划

为兼顾工业机器人工作效率与轨迹的平稳性,提出一种基于混合遗传算法的二次轨迹规划方案.通过最优时间轨迹规划得到最小执行时间,在最小执行时间内进行最优冲击轨迹规划,进而规划出一条既高效又平滑的运动轨迹.采用五次均匀B样条在关节空间进行快速插值,不仅保证了各关节速度和加速度连续性还保证了各关节冲击的连续性.连续平滑的冲击可以减少机械振动,延长机器人的工作寿命.选用PUMA560为对象进行仿真与实验,结果表明,该方案可以获得比较理想的机器人运动轨迹,所提出的混合遗传算法能有效提高全局寻优的性能和算法运行的稳定性.     

基于压电陶瓷的柔性机器人主动抑振控制策略研究

柔性机器人因其轻质、高效、低能耗等优点已被广泛应用于航空航天,工业制造等诸多领域。然而,柔性机构易产生弯曲变形,引起系统振动而大大降低机器人的工作精度。为提高柔性机器人的工作性能,多种抑振策略得以研究与应用。提出了基于压电陶瓷（PZT）的柔性机器人振动主动抑制策略。其中,PZT传感器和PZT制动器分别被用来检测和抑制柔性臂的振动。本文构建了基于PZT材料的单自由度柔性机械臂的理论模型,并获得了传感电压与制动电压的传递函数。设计了一个可变控制方案的抑振器以抑制系统在不同频率下的振动。在COMSOL中进行仿真,获得了系统的抑振率。根据仿真结果显示,柔性臂在前三阶振动下,臂的末端位移分别得到了57.04%,57.76%与58.96%的抑制;系统的动能得到了57.95%,71.19%与87.81%的抑制。     

基于解耦的工业机器人模糊PID抑振研究

该文针对工业机器人在定位过程中由于关节柔性产生的振动抑制问题，对六自由度的工业机器人进行研究，提出了基于解耦的柔性关节模糊PID抑振控制算法。首先，建立了工业机器人系统的动力学模型；然后，根据连杆之间的耦合关系设计了变参数模糊控制器，降低各连杆之间的耦合程度，并在解耦的基础上加入模糊PID控制器，对解耦后的各个关节进一步抑振；最后，通过Simulink仿真验证该算法的有效性。研究结果表明，变参数模糊解耦比定参数模糊解耦的效果更好，解耦之后的转台、大臂和小臂之间可以近似看成线性系统，再进行模糊PID控制，其抑振的效果相比传统PID控制器来说更为理想。     

笛卡尔空间轨迹平滑过渡的前瞻插补算法

为了解决由于六轴串联工业机器人由于笛卡尔空间运动轨迹不平滑导致频繁启停的问题,提出了基于三次准均匀B样条曲线的前瞻插补算法实现轨迹平滑过渡和提高运行效率。该算法采用三次准均匀B样条曲线作为笛卡尔空间中相邻轨迹的过渡曲线,根据过渡曲线的曲率求出过渡曲线的速度约束,利用速度前瞻根据各轨迹段长度规划出合适的衔接速度,对各轨迹段分别采用非对称S曲线加减速控制,通过等时插补获得实际插补点。在六轴串联工业机器人的控制平台上进行实验验证,结果表明,相较于传统算法,该算法可以使六轴串联工业机器人在笛卡尔空间的运动轨迹更加连续与平滑,运行效率得到了有效提升。     

任务空间实时轨迹规划的旋量方法

：基于旋量提出了一种任务空间实时轨迹规划的新算法．该算法借鉴了机器人制导的设计思想,以 空间机器人目标捕获为应用背景,可以仅依靠视线测量信息实现多种约束条件下的轨迹规划．首先给出了矢 量的旋量表示方法,在此基础上设计了一种类似于比例导引的新型三维制导律．应用新型三维制导律计算出 运动的法向加速度,并根据安全性的要求计算出线加速度;两者结合完成了轨迹生成的实时算法．生成的轨 迹安全可行,且具有一定的优化特性．仿真结果证明了该规划算法的有效性．     

基于PSO的工业机器人时间-脉动最优轨迹规划

为提高工业机器人的工作效率,并且保持机器人关节平稳运动,提出一种基于粒子群优化算法的时间-脉动最优轨迹规划方案;通过权重法将多目标优化转化为单目标优化,再运用粒子群优化算法得到时间-脉动最优的运动轨迹;轨迹规划中,采用了关节空间五次非均匀B样条插值法,以确保脉动曲线的连续性;最后以GRB4016工业机器人为研究对象进行仿真实验,结果表明,该方案可以得到较理想的运动轨迹,并验证了方案的有效性。     

Time-optimal and jerk-continuous trajectory planning for robot manipulators with kinematic constraints

In this paper a high smooth trajectory planning method is presented to improve the practical performance of tracking control for robot manipulators. The strategy is designed as a combination of the planning with multi-degree splines in Cartesian space and multi-degree B-splines in joint space. Following implementation, under the premise of precisely passing the via-points required, the cubic spline is used in Cartesian space planning to make either the velocities or the accelerations at the initial and ending moments controllable for the end effector. While the septuple B-spline is applied in joint space planning to make the velocities, accelerations and jerks bounded and continuous, with the initial and ending values of them configurable. In the meantime, minimum-time optimization problem is also discussed. Experimental results show that, the proposed approach is an effective solution to trajectory planning, with ensuring a both smooth and efficiency tracking performance with fluent movement for the robot manipulators.     

一种新颖的笛卡尔空间轨迹规划方法

本文通过对螺旋理论和空间样条曲线生成原理的有机结合，提出了一种“虚拟关节” 的概念，在此基础上给出了一种新颖的笛卡尔空间的机器人轨迹规划方法．由于这种方法综 合了关节空间轨迹规划和笛卡尔空间轨迹规划各自所具有的优点，因此既简单又直观．而且 ，利用该方法可以很容易地得到一条经过所有控制点并满足所要求边界条件的空间轨迹．为 验证其有效性，本文基于一种9自由度模块化机器人平台给出了具体的实验方法和结果．     

Cooperative Control of a 3D Dual-Flexible-Arm Robot

This paper discusses cooperative control of a dual-flexible-arm robot to handle a rigid object in three-dimensional space. The proposed control scheme integrates hybrid position/force control and vibration suppression control. To derive the control scheme, kinematics and dynamics of the robot when it forms a closed kinematic chain is discussed. Kinematics is described using workspace force, velocity and position vectors, and hybrid position/force control is extended from that on dual-rigid-arm robots. Dynamics is derived from constraint conditions and the lumped-mass-spring model of the flexible robots and an object. The vibration suppression control is calculated from the deflections of the flexible links and the dynamics. Experiments on cooperative control are performed. The absolute positions/orientations and internal forces/moments are controlled using the robot, each arm of which has two flexible links, seven joints and a force/torque sensor. The results illustrate that the robot handled the rigid object damping links' vibration successfully in three-dimensional space.     

Design of walking gaits for Tao-Pie-Pie,a small humanoid robot

A new way for multi-axis robot trajectory planning using a single cubic spline incorporating velocity and acceleration clipping is presented. Equations for velocity and acceleration clipping employing the cubic spline function for a single axis are derived. A robot tool-tip velocity vector magnitude clipping algorithm is proposed. Implementation for a fly-by and contour following trajectory control is discussed.     

Dynamics and Noncollocated Model‐Free Position Control for a Space Robot with Multi‐Link Flexible Manipulators

In this paper, both the dynamics and noncollocated model‐free position control (NMPC) for a space robot with multi‐link flexible manipulators are developed. Using assumed modes approach to describe the flexible deformation, the dynamic model of the flexible space robotic system is derived with Lagrangian method to represent the system dynamic behaviors. Based on Lyapunov's direct method, the robust model‐free position control with noncollocated feedback is designed for position regulation of the space robot and vibration suppression of the flexible manipulators. The closed‐loop stability of the space robotic system can be guaranteed and the guideline of choosing noncollocated feedback is analyzed. The proposed control is easily implementable for flexible space robot with both uncertain complicated dynamic model and unknown system parameters, and all the control signals can be measured by sensors directly or obtained by a backward difference algorithm. Numerical simulations on a two‐link flexible space robot are provided to demonstrate the effectiveness of the proposed control.     

Optimal trajectory generation algorithm for serial and parallel manipulators

In this paper, an Optimal Trajectory Generation Algorithm (OTGA) is developed for generating minimum-time smooth motion trajectories for serial and parallel manipulators. OTGA is divided into two phases. The first phase encompasses derivation of minimum-time optimal trajectory using cubic spline due to its less vibration and overshoot characteristics. Although cubic splines are widely used in robotics, velocity and acceleration ripples in the first & last knots can worsen manipulator trajectory. The second phase includes changing cubic spline interpolation in the first and last knots of optimized trajectory with 7th order polynomial for having zero jerk at the beginning and end points of trajectory. Performing this modification eliminate undesired worsening in the trajectory and provide smoother start and stop of joint motions. Particle Swarm Optimization (PSO) is chosen as optimization algorithm because of its easy implementation and successful optimization performance. OTGA has been tested in simulation for PUMA robot and results are compared with algorithms proposed by earlier authors. In addition, a discrete-time PID control scheme for PUMA robot is designed for comparing energy consumption of OTGA with algorithms developed by previous authors. Comparison results illustrated that OTGA is the better trajectory generation algorithm than the others.     

Reinforcement learning based on movement primitives for contact tasks

Recently, robot learning through deep reinforcement learning has incorporated various robot tasks through deep neural networks, without using specific control or recognition algorithms. However, this learning method is difficult to apply to the contact tasks of a robot, due to the exertion of excessive force from the random search process of reinforcement learning. Therefore, when applying reinforcement learning to contact tasks, solving the contact problem using an existing force controller is necessary. A neural-network-based movement primitive (NNMP) that generates a continuous trajectory which can be transmitted to the force controller and learned through a deep deterministic policy gradient (DDPG) algorithm is proposed for this study. In addition, an imitation learning algorithm suitable for NNMP is proposed such that the trajectories similar to the demonstration trajectory are stably generated. The performance of the proposed algorithms was verified using a square peg-in-hole assembly task with a tolerance of 0.1 mm. The results confirm that the complicated assembly trajectory can be learned stably through NNMP by the proposed imitation learning algorithm, and that the assembly trajectory is improved by learning the proposed NNMP through the DDPG algorithm.     

基于hp自适应伪谱法的空间机器人路径规划

针对空间机器人运动过程中基座姿态产生较大扰动的问题,基于hp自适应高斯伪谱法提出了一种以基座所受反作用力矩最小为目标函数的空间机器人路径规划方法.首先,综合考虑空间机器人运动过程中存在的关节角度约束、关节角速度约束、控制力矩约束及初始状态和终端状态约束等约束条件,将空间机器人路径规划问题看成满足一系列约束条件和边界条件并实现特定性能指标最优的最优控制问题.其次,结合hp自适应高斯伪谱法（hp-AGPM）与非线性规划技术,求解带有边界约束和路径约束的优化控制问题,得到满足约束且性能指标最优的空间机器人运动轨迹.最后,以平面2自由度空间机械臂为例对所设计方法进行仿真验证,并与其他伪谱法进行对比分析.仿真结果表明：本文算法能在10.6 s的时间内规划出满足各约束条件且容许偏差低于10^-6的最优运动轨迹,并且在计算速度和配点数量上都优于其他伪谱法.