轻工业包装物品搬运机器人路径跟踪控制

目的 为了提高直角坐标搬运机器人的定位精度,保证机器人能够按照预定路径运动。方法 介绍直角坐标机器人工作原理,并基于模糊控制理论,提出一种基于模糊PID的直角坐标机器人轨迹跟踪控制算法,并将其应用于机器人运动轨迹跟踪控制中。结果 仿真和实验结果表明,基于模糊PID的机器人控制器能够保证机器人沿预定路径运动,机器人轨迹跟踪误差能够很快收敛于0附近,该轨迹跟踪方法具有较好的抗干扰性和鲁棒性。结论 所提方法能够明显提高直角坐标机器人的路径跟踪能力,对于提升机器人运动精度具有参考价值。     

分级随机采样弱随机RRT算法及在移动机器人运动规划中的应用

针对移动机器人运动规划过程中,采用快速扩展随机树(RRT)算法采样效率低,寻找临近节点计算量大,及非线性反馈控制器不受系统模型动态约束的问题, 提出一种新的基于分级随机采样与扩展的弱随机RRT算法,同时设计快速限幅非线性反馈控制器,保证运动规划过程中机器人始终满足系统模型动态约束。首先,在迭代伊始结合节点评价策略建立节点的选取集合;其次,按照规定顺序选取扩展节点并随机选择扩展方向,将计算得到的新子节点连接到随机树完成扩展;然后,对初始路径进行规划,采用快速限幅非线性反馈控制器计算机器人在路径点上的控制序列和位姿,实现移动机器人的运动规划;最后,通过仿真验证了该算法的有效性。结果表明:提出的分级随机采样弱随机RRT算法不依赖最近节点的选取,相比RRT算法缩短了求解时间,提高了迭代速度。     

欠驱动搬运机器人轨迹跟踪控制

目的为了解决欠驱动搬运机器人的中心和质心不重合的轨迹跟踪问题。方法建立非完整性约束的欠驱动机器人的运动学和动力学的模型,基于反步法控制策略生成新的虚拟反馈量,设计跟踪控制器,同时,利用自适应技术对具有不确定跟踪控制器的参数进行校正,通过Lyapunov理论验证控制器的稳定性。结果仿真实验结果表明,欠驱动搬运机器人的实际轨迹可以快速地跟踪期望轨迹,验证了基于反步法设计的跟踪控制器的可行性和有效性。结论设计的控制器能够使搬运移动机器人达到良好的轨迹跟踪效果,并且保证了控制器的自适应性。     

High performance loading robot design for a tool-delivery system

A concept of an ultrafast distributed material transfer system based upon linear induction motors (LIM) has been proposed in which vehicles can travel at velocities of up to 120 km/h. Performance and economic analysis of a high-speed tool-delivery system based on such a system has shown that the robot manipulator that loads and unloads the vehicles is the bottleneck. This paper presents a method to design a high-speed robot with cycle times comparable with the LIM material transfer system. A generic design methodology is developed for robot manipulators that integrates several key design issues such as kinematics, dynamics, structural mechanics, actuator sizing, assessing robustness to parameters and sensor errors, and vibration analysis. The methodology is computationally efficient and has been implemented using MATLAB for evaluating a number of 'rough-cut' feasible designs for the high-speed robot. A highly distributed architecture and distributed protocols are proposed for integrating the high-speed robot and the high-speed material transfer system.     

面向大型机场草坪的割草机器人路径规划及轨迹跟踪控制研究

为了提高割草机器人的工作效率及环境适应能力,基于移动机器人平台设计了一种既受遥控操作又能自主运行的适用于大型机场草坪作业的割草机器人。首先,运用高精度差分GPS（global positioning system,全球定位系统）采集机场草坪边界和障碍物的位置信息,根据采集的信息将机场草坪分为最少数目的凸多边形工作区域;考虑到割草机器人无法原地无半径转弯,在传统迂回式路径规划算法的基础上提出一种往返直线型路径规划算法,并在凸多边形路径规划区内推导出遍历路径的显示方程表达式。其次,运用高精度差分GPS测得割草机器人实际轨迹并与规划轨迹对比,设计了一种区间判断型轨迹纠偏算法;以执行电机的PID（proportion integration differentiation,比例积分微分）控制和区间判断型轨迹纠偏算法构造割草机器人双闭环轨迹跟踪控制器,对按传统迂回式路径和往返直线型路径行进的割草机器人进行轨迹跟踪仿真分析。最后,以自制的割草机器人为例,按往返直线型路径运行方式进行样机实验。仿真结果发现：当割草机器人跟踪当前路径到达终点后会自动调头跟踪下一条路径,验证了轨迹跟踪算法的稳定性;传统迂回式路径运行方式下割草机器人的漏割率较高,达到46.42%,而往返直线型路径运行方式下其漏割率为7.15%,明显优于传统迂回式路径仿真结果。样机实验测得的漏割率为8.89%,与仿真实验结果一致,表明所设计的轨迹跟踪算法对大型机场草坪作业割草机器人是适用的。研究结果可为大型机场草坪割草机器人的开发提供理论指导。     

基于改进A*算法的仓储物流移动机器人 任务调度和路径优化研究

为解决仓储物流中移动机器人执行订单任务过程中,调度系统难以快速准确地进行任务分配,且搬运路线并非最短最优路线的问题,根据移动机器人的运动方式和订单任务要求,构建具有可重构性的仓库空间模型和栅格地图模型,通过建立数学模型求解订单任务最短完工时间分配问题,改进传统A^*算法中3种常用距离算法的不足,并提出复杂对角线距离算法进行路径规划仿真。仿真结果表明,上述方法实现总任务完工时间最短的任务分配,使路径规划搜索节点数减少30%,路径长度缩短20%。     

未知环境下基于三次螺线Bug算法的移动机器人路径规划

研究了环境未知情况下的移动机器人实时路径规划问题,将Bug算法与基于滚动窗口的路径规划相结合,提出了一种改进的移动机器人路径规划方法。详细分析了三次螺线作为移动机器人跟踪路径所具有的各种优异的几何特性,定义路径光滑成本函数,利用三次螺线对滚动窗口内规划的路径光滑化,使得移动机器人易于跟踪所规划的路径,扩展了移动机器人的应用领域。最后对本文算法的收敛性和完备性予以证明。仿真实验验证了该方法的有效性。     

PRODUCTION PLANNING AND CONTROL HIERARCHY USING A GENERIC CONTROLLER

An enhanced decision-making and control hierarchy is introduced for the production planning problem. The proposed decomposition schema first combines the principles of both a temporal decomposition and a product disaggregation to define the production planning hierarchy. The concept of a generic controller is then applied to two levels of hierarchical decision making. To further provide for enhanced decision making and control, both the frequency and the content of coordinative information exchanges among the hierarchical levels have been significantly augmented. An integrated, stochastic decision-making approach will be employed within each implemented generic controller to rigorously address the uncertainties that arc inherent to the production planning problem. The proposed two-level application of the generic controller is then expanded to outline the interactions among additional planning levels as well as other functions comprising a computer-integrated manufacturing system. Finally, methods are proposed for determining the essential planning horizon lengths that are required for each production-planning level to interact with other manufacturing functions.     

储罐探伤爬壁机器人全遍历路径规划方法

储罐探伤爬壁机器人全遍历路径规划要求机器人高效遍历储罐外壁全部无障碍物区域。结合邻接矩阵、路径选择函数,提出一种单元分解算法并应用于爬壁机器人路径规划中。首先,将爬壁机器人的工作环境简化为二维平面,并通过分析漏检面积确定机器人遍历基本路径;接着,建立栅格环境,对每个栅格赋予x_i值以表示其栅格状态;其次,采用矩形分解法将工作环境划分为若干子区域,通过图的深度优先搜索算法和邻接矩阵确定各子区域的衔接顺序;最后,在子区域的遍历和切换过程中,引入方向函数y_i来判断爬壁机器人是否陷入死区,结合x_i值提出路径选择函数f_i以引导爬壁机器人快速逃离死区。在虚拟环境中进行了仿真实验,仿真结果表明,该方法不仅能引导爬壁机器人以高覆盖率和低重复率遍历工作区域,而且能快速地逃离死区。全遍历路径规划的实现拓展了爬壁机器人在检测储罐罐壁中的应用。     

机器人滚动路径规划的算法与仿真研究

借鉴预测控制滚动优化原理，研究了未知环境中移动机器人路径规划问题。文中提出的基于滚动窗口的移动机器人路径规划方法充分利用机器人实时测得的局部环境信息，以滚动方式进行在线规划。大量仿真结果表明，滚动规划使机器人对动态环境具有很好的适应性，但由于缺乏全局环境信息，在有些复杂情况下不能保证规划的顾利实施，需要进一步增加环境约束和对已探知信息的记忆。     

基于遗传算法的码垛机器人路径规划应用

目的为了改进传统遗传算法在码垛机器人路径规划中可能出现的局部陷阱和过早收敛问题,以及机器人的能耗和路线平滑性问题,提出一种改进的遗传算法机器人路径规划方法。方法针对传统遗传算法存在的问题,分别对种群初始化、适应度函数、选择算子、交叉算子、变异算子的算法和方式进行调整和改进,对优秀算法进行融合。针对基本遗传算法主要着重于路径最短,从而忽视了机器人的能耗及路径平滑性等问题,设计一种综合考虑距离和转弯次数控制的适应度函数,最后将改进的算法应用于码垛机器人的路径规划中。结果仿真结果表明,相较于基本遗传算法,提出的算法搜索到的路径质量更高,不仅距离更短,同时转弯次数远远小于其他算法,路径更为平滑,验证了该算法的有效性。结论基于该算法的码垛机器人路径在兼顾距离最优的同时,路线更加平滑。由于减少了转向次数,机器人的能耗更低,同时仿真结果表明,该算法的实时性也较好。     

基于动态运动基元的移动机器人路径规划

针对二维环境下移动机器人路径规划问题,提出一种基于动态运动基元(DMPs)的路径规划方法。该方法首先用手柄来控制机器人,记录机器人的运动轨迹,然后将记录的轨迹作为DMPs算法的学习样本,利用轨迹样本进行训练获得DMPs算法的模型参!,从而实现机器人的路径规划。当运动环境中有障碍物时,在已有学习基础上通过设计耦合因子规划出避障路径,在此基础上,改变机器人运动的目标位置,可以完成对新目标的泛化推广。仿真和实验结果表明,DMPs算法在移动机器人路径规划上具有可行性。     

应用于圆饼工件分拣的码垛机器人自适应积分滑模控制

目的 针对存在系统未建模特性和负载变化下码垛机器人关节空间轨迹跟踪控制的问题,设计一种基于结合时延估计技术与自适应积分滑模面的控制策略。方法 根据圆饼工件分拣需求,设计一款桌面式码垛机器人系统,推导机器人的运动学与动力学模型,给出关节空间轨迹规划算法,并基于无模型思想设计关节空间轨迹跟踪控制器。结果 利用雅克比伪逆法可反解出机器人的关节角;通过所提的轨迹规划算法能有效获得各关节运动轨迹;与PID控制器和积分滑模控制器相比,文中所提控制器具有较好的控制精度、较强抗干扰性和较高的鲁棒性。结论 仿真和实验结果表明,所设计的基于时延估计技术的自适应积分滑模控制器是合理的,能使得码垛机器人完成圆饼工件的分拣任务,具有一定的工程应用价值。     

Novel Algorithm for Mobile Robot Path Planning in Constrained Environment

This paper presents a development of a novel path planning algorithm, called Generalized Laser simulator (GLS), for solving the mobile robot path planning problem in a two-dimensional map with the presence of constraints. This approach gives the possibility to find the path for a wheel mobile robot considering some constraints during the robot movement in both known and unknown environments. The feasible path is determined between the start and goal positions by generating wave of points in all direction towards the goal point with adhering to constraints. In simulation, the proposed method has been tested in several working environments with different degrees of complexity. The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. The results revealed that the proposed method has shortest path length, less computational time and the best smooth path. As an average, GLS is faster than A* and LS by 7.8 and 5.5 times, respectively and presents a path shorter than A* and LS by 1.2 and 1.5 times. In order to verify the performance of the developed method in dealing with constraints, an experimental study was carried out using a Wheeled Mobile Robot (WMR) platform in labs and roads. The experimental work investigates a complete autonomous WMR path planning in the lab and road environments using a live video streaming. Local maps were built using data from a live video streaming with real-time image processing to detect segments of the analogous-road in lab or real-road environments. The study shows that the proposed method is able to generate shortest path and best smooth trajectory from start to goal points in comparison with laser simulator.     

Control of Velocity-Constrained Stepper Motor-Driven Hilare Robot for Waypoint Navigation

Finding an optimal trajectory from an initial point to a final point through closely packed obstacles, and controlling a Hilare robot through this trajectory, are challenging tasks. To serve this purpose, path planners and trajectory-tracking controllers are usually included in a control loop. This paper highlights the implementation of a trajectory-tracking controller on a stepper motor-driven Hilare robot, with a trajectory that is described as a set of waypoints. The controller was designed to handle discrete waypoints with directional discontinuity and to consider different constraints on the actuator velocity. The control parameters were tuned with the help of multi-objective particle swarm optimization to minimize the average cross-track error and average linear velocity error of the mobile robot when tracking a predefined trajectory. Experiments were conducted to control the mobile robot from a start position to a destination position along a trajectory described by the waypoints. Experimental results for tracking the trajectory generated by a path planner and the trajectory specified by a user are also demonstrated. Experiments conducted on the mobile robot validate the effectiveness of the proposed strategy for tracking different types of trajectories.     

包装搬运机器人运动轨迹优化设计

目的为提高包装搬运机器人的运动精度,提出基于改进S型曲线的包装机器人轨迹曲线的规划方法。方法首先分析包装搬运机器人的工艺要求,以码垛机器人为研究对象,重点讨论轨迹规划问题,采用改进S型曲线实现了码垛机器人轨迹规划。为进一步提高机器人运行效率,基于遗传算法对整个运动过程所需时间进行优化并给出了具体优化过程。最后,搭建实验平台并进行相关实验研究。结果实验结果表明,基于所述轨迹规划方法,码垛机器人的重复定位精度可以达到0.5 mm,运动过程无速度和加速度突变,机器人运行平稳。结论该控制系统有效提高了包装机器人的运行效率,对于机器人稳定可靠运行具有重要意义。     

Double global optimum genetic algorithm–particle swarm optimization-based welding robot path planning

Spot-welding robots have a wide range of applications in manufacturing industries. There are usually many weld joints in a welding task, and a reasonable welding path to traverse these weld joints has a significant impact on welding efficiency. Traditional manual path planning techniques can handle a few weld joints effectively, but when the number of weld joints is large, it is difficult to obtain the optimal path. The traditional manual path planning method is also time consuming and inefficient, and cannot guarantee optimality. Double global optimum genetic algorithm–particle swarm optimization (GA-PSO) based on the GA and PSO algorithms is proposed to solve the welding robot path planning problem, where the shortest collision-free paths are used as the criteria to optimize the welding path. Besides algorithm effectiveness analysis and verification, the simulation results indicate that the algorithm has strong searching ability and practicality, and is suitable for welding robot path planning.     

面向仓库货架的商品智能拣选机器人设计

目的 为降低仓储拣选作业的劳动强度、提高拣选准确率,设计一款可代替人工拣货的拣选机器人。方法 基于PaddlePaddle的PP-ShiTu图像识别系统,实现货架商品的精确识别和种类的快速更新;针对低成本机械臂的视觉抓取问题,提出基于“无标定3D视觉+AGV运动控制”的货架商品抓取引导方法;采用二维码自主导航和智能升降系统实现了货架商品的搬运和立体抓取。结果 实验证明,所设计的拣选机器人实现了货架商品的精确抓取和搬运,测试准确率达到了92.25%。结论 基于该方法构建的智能拣选机器人,可以完成仓库货架商品的拣选和搬运。     

储罐检测爬壁机器人全遍历路径规划

针对爬壁机器人难以在储罐外壁实现全遍历检测的问题,提出了一种基于滚动窗口的优先级启发式路径规划算法。在滚动的可视窗口内基于栅格地图进行环境建模,利用优先级启发式算法在滚动的规划窗口内实现对遍历路径的搜索;针对环境中存在U型障碍物的情况,进行了U型障碍物识别和U型障碍物区域直接填充;当机器人陷入死区时,采用死区逃离算法使机器人顺利逃离死区。仿真结果表明,该路径规划方法能指导爬壁机器人在未知储罐外壁环境的情况下实现高效全遍历。研究结果对提高爬壁机器人在储罐外壁的遍历效率具有一定的理论和工程意义。     

基于ARM的嵌入式包装搬运机器人控制系统设计

目的为提高包装物品生产效率,提升直角包装搬运机器人的稳定性、可靠性和运动精度。方法根据四自由度直角坐标型包装搬运机器人的机械结构和功能需求,设计一款基于ARM嵌入式的直角包装搬运机器人控制系统。控制系统硬件由主控制器ARM,FPGA和示教器ARM组成,主控制器ARM通过串口与FPGA、示教器ARM以及伺服系统进行通讯。同时基于上述硬件结构提出一种改进型S曲线插值速度控制方法。结果实验结果表明,该控制系统下的直角包装搬运机器人定位精度为±0.5 mm,完全满足设计要求。结论该控制系统能够满足实际作业需求,提升了包装效率,降低了成本。