基于准确度评估的7自由度手术机器人术前摆位优化算法

针对微创机器人辅助的外科手术复杂的术前摆位问题,以甲状腺微创手术用到的床旁双7自由度协作机器人为研究对象,将机械臂的运动准确度以及运动学性能作为优化目标,提出了机械臂准确度评估指标以及其对应的干涉指数,并提出了一套基于带精英策略的非支配排序遗传算法（NSGA-Ⅱ）多目标遗传算法的术前规划方法。最后,将由该遗传算法优化得...     

Time-optimal tool motion planning with tool-tip kinematic constraints for robotic machining of sculptured surfaces

A time-optimal motion planning method for robotic machining of sculptured surfaces is reported in this paper. Compared with the general time-optimal robot motion planning, a surface machining process provides extra constraints such as tool-tip kinematic limits and complexity of the curved tool path that also need to be taken into account. In the proposed method, joint space and tool-tip kinematic constraints are considered. As there are high requirements for tool path following accuracy, an efficient numerical integration method based on the Pontryagin maximum principle is adopted as the solver for the time-optimal tool motion planning problem in robotic machining. Nonetheless, coupled and multi-dimensional constraints make it difficult to solve the problem by numerical integration directly. Therefore, a new method is provided to simplify the constraints in this work. The algorithm is implemented on the ROS (robot operating system) platform. The geometry tool path is generated by the CAM software firstly. And then the whole machine moving process, i.e. the feedrate of machining process, is scheduled by the proposed method. As a case study, a sculptured surface is machined by the developed method with a 6-DOF robot driven by the ROS controller. The experimental results validate the developed algorithm and reveal its advantages over other conventional motion planning algorithms for robotic machining.     

电能表检验台体串联机械臂时间最优轨迹规划

时间最优轨迹规划有助于缩短机械臂运动时间,提高工作效率,在机械臂实际应用场景中起着至关重要的作用.针对串联机械臂点到点运动的时间最优轨迹规划问题,提出一种基于改进多种群遗传算法的最优轨迹规划方法.通过五次多项式插值对机械臂运动路径进行拟合,利用改进的多种群遗传算法对机械臂运动时间进行优化,改进之处包括:设计含有惩罚项的...     

Comparison of surface roughness quality obtained by high speed CNC trimming and high speed robotic trimming for CFRP laminate

This paper proposes an experimental approach for evaluating the surface roughness of the CFRP parts produced by high speed CNC trimming and high speed robotic trimming under various cutting conditions. A comparison is made between the surface roughnesses obtained by the two processes. The results obtained show that, the measured profiles obtained from high speed robotic trimming are dominated by a large trajectory deviation, as compared to machine tool trimming results. After the trajectory deviation effect is discounted, the results show that for the +45° ply orientation, the surface quality obtained through high speed robotic trimming is similar to what is obtained with the CNC machine. Furthermore, a significant relationship was observed between the surface quality and the ply orientation, whatever the machining process and the cutting conditions employed. The −45° ply orientation represents the worst case in terms of surface roughness, whatever the machining process. It is 4 times higher compared with that of +45° ply orientations,The results also show that the effect of cutting conditions on surface quality is significant for both machining processes tested.     

Enhancement and evaluation in path accuracy of industrial robot for complex surface grinding

Lower path accuracy is an obstacle to the application of industrial robots in intelligent and precision grinding complex surfaces. This paper proposes a novel path accuracy enhancement strategy and different evaluation methods for a six-degree-of-freedom industrial robot FANUC M710ic/50 used for grinding an aero-engine blade. Six groups of theoretical tool paths individually planned on this complex surface were obtained using the iso-parametric method and the constant chord height method. Then the actual paths of the robot were dynamically recorded by a laser tracker with a high frequency. A revised Levenberg-Marquardt and Differential Evolution hybrid algorithm was proposed to improve the absolute robotic positioning accuracy by considering the average curvature variation rate, the arc length and the number of cutter contact points on planning paths. The results showed that the maximum positioning error had been drastically reduced from 0.792 mm to 0.027 mm. Based on the redefinition of robotic path accuracy, including position accuracy and shape accuracy in this work, the methods MP-TLD, BP-TPD and MP-TID were proposed to evaluate the enhanced path accuracy. The evaluation results showed that the different path planning methods have almost little effect on path accuracy. Furthermore, the maximum path deviation evaluated by the MP-TLD method was reduced from 0.378 mm to 0.044 mm, evaluated by the BP-TPD method was reduced from 0.374 mm to 0.029 mm, and evaluated by the MP-TID method was reduced from 0.205 mm to 0.026 mm. It is concluded that these evaluation methods are basically valid and the average path accuracy value is about 0.035 mm, for present complex surface grinding with this typical industrial robot. Finally, the robotic grinding experiments of titanium alloy blades are conducted to further validate the effectiveness of the proposed method.     

结合IMask R-CNN的绳驱机械臂视觉抓取方法研究

绳驱超冗余机械臂具有灵活性强、工作空间大等特点,在航天活动中可替代宇航员进行各种航空作业.以空间飞行器在轨维修为研究背景,模拟其实验环境,设计了一套基于RGB-D的可移动绳驱超冗余机械臂定位抓取系统.首先改进了Mask R-CNN算法,在保证检测精度的同时降低模型尺寸,通过Intel RealSense D435 i采集图像输入到目标检测模型得到目标的类别和位置信息,进一步利用自适应末端位置更新算法递推机械臂的正逆运动学模型,并结合轨迹规划完成目标的三维空间定位和抓取.实验结果表明,改进后的Mask R-CNN算法能在保证精度的情况下有效地降低模型尺寸,抓取系统的逆运动学求解速度快,具有较好的定位精度,能够有效地完成飞行器抓取的任务.     

An adaptive trajectory planning algorithm for robotic belt grinding of blade leading and trailing edges based on material removal profile model

Robotic belt grinding of the leading and trailing edges of complex blades is considered to be a challenging task, since the microscopic material removal mechanism is complicated due to the flexible contact state accompanied with greatly varying curvature that finally affects the machined profile accuracy. The resulting poor accuracy of blade edges, to a great extent, is attributed to the trajectory planning method which less considers the dynamics. In this paper, an iso-scallop height algorithm based on the material removal profile (MRP) model is developed to plan the tool paths by taking into consideration the elastic deformation at contact wheel-workpiece interface. An improved constant chord-height error method considering the influence of elastic deformation is then proposed to adaptively plan the grinding points according to the curvature change characteristics of the free-form surface. Based on these two steps, a MRP model based adaptive trajectory planning algorithm is constructed to enhance the profile accuracy facing the robotic belt grinding operation. Simulation and experimental results demonstrate the effectiveness of the proposed trajectory planning algorithm for the robotic belt grinding of blades from the perspectives of surface roughness, profile accuracy and processing efficiency. Particularly this technology serves to solve the problem of over-cutting at the blade leading and trailing edges.     

A Topological Implementation for Motion Planning of a Robotic Arm

An efficient path planning algorithm based on topologic method is presented in this paper.The collision free path planning for three-joint robotic arm consists of three parts:partition of C-space,construction of CN and search for a path in CN.We mainly solved the problems of partitioning the C-space and undging the connectivity between connected blocks,etc.For the motion planning of a robotic arm with a gripper,we developed the concepts of global planning and local planning,and discussed the basic factors for constructing the planning system.In the paper,some evaluation and analysis of the complexity and reliability of the algorithm are given,together with some ideas to improve the efficiency and increase the reliability.At last,some experimental results are pesented to show the efficency and accuracy of the algorithm.     

Mechanical design and control of inflatable robotic arms for high positioning accuracy

In recent years, inflatable robotic arms have been developed so that physical contact with humans and working environments could be performed safety. In industry, there is a growing demand for safe industrial robots to collaborate with people and work in various environments. In general, however, the positioning accuracy of inflatable robotic arms has not been discussed. This paper proposes an inflatable link structure and a non-inflatable joint structure that could realize a high positioning accuracy for such robotic arms. This paper experimentally demonstrates that these structures can improve positioning accuracy. In addition to these structures, the joint torque characteristics of the inflatable robotic arms were investigated. In order to perform accurate motion control, a visual feedback control method was introduced for inflatable robotic arms. The mechanism and control system used in this paper can improve the positioning accuracy performance of inflatable robots. A 2-DOF inflatable robotic arm and a camera system were found to be able to achieve a high positioning accuracy (i.e. less than 1 mm).     

多机器人覆盖技术研究进展

系统地总结了当前覆盖问题的定义、分类和应用前景.对多机器人覆盖中关于通信、环境地图、路径规划算法及效果评价等方面的研究进展情况进行了阐述.分析并指出若干多机器人覆盖研究中的重点和难点问题:体系结构、通信技术、协商协作、地图表示、路径规划及效果评价,并对未来的研究发展方向进行了探讨.     

改进RRT-人工势场法的机械臂堆垛运动方法

快速拓展随机树算法(RRT)在机械臂路径规划中存在随机性强、搜索效率低、规划路径长等问题,不能在货柜堆垛场景中取得相对最优的光滑路径.对此,该文提出了一种改进RRT-人工势场法混合算法进行货柜堆垛机械臂运动规划.首先,对传统快速拓展随机树算法进行改进,在传统快速拓展随机树算法的全局搜索的基础上引入目标搜索,增强了随机树...     

Constrained Motion Model of Mobile Robots and Its Applications

Target detecting and dynamic coverage are fundamental tasks in mobile robotics and represent two important features of mobile robots: mobility and perceptivity. This paper establishes the constrained motion model and sensor model of a mobile robot to represent these two features and defines the k -step reachable region to describe the states that the robot may reach. We show that the calculation of the k-step reachable region can be reduced from that of 2^k reachable regions with the fixed motion styles to k + 1 such regions and provide an algorithm for its calculation. Based on the constrained motion model and the k -step reachable region, the problems associated with target detecting and dynamic coverage are formulated and solved. For target detecting, the k-step detectable region is used to describe the area that the robot may detect, and an algorithm for detecting a target and planning the optimal path is proposed. For dynamic coverage, the k-step detected region is used to represent the area that the robot has detected during its motion, and the dynamic-coverage strategy and algorithm are proposed. Simulation results demonstrate the efficiency of the coverage algorithm in both convex and concave environments.     

Comparison of intelligent control planning algorithms for robot's part micro-assembly task

Two intelligent control (path or motion) planning algorithms, based on a neural network and a fuzzy set theory, related to a robotic quasi-static part micro-assembly task are introduced. The part micro-assembly considered in this paper consists in a mating a part with an assembly hole or a receptacle (target) without a jamming. These algorithms are then compared through the utilization of experimentally measured data as well as simulations and a set of criteria. An entropy function, which is a useful measure of the variability and the information in terms of uncertainty, is introduced to measure its overall performance of a task execution related to the part micro-assembly task. Fuzzy set theory is introduced to address the uncertainty associated with the part micro-assembly procedure. The degree of uncertainty associated with the part micro-assembly is used as an optimality criterion, e.g. minimum fuzzy entropy, for a specific task execution. It is shown that the machine organizer using a sensor system can intelligently determine an optimal control value, based on explicit performance criteria. The algorithms utilize knowledge processing functions such as machine reasoning, planning, inferencing, learning, and decision-making. The results show the effectiveness of the proposed approaches. The proposed techniques are applicable to a wide range of robotic tasks including motion planning, pick and place operations, and part mating with various shaped parts.     

空间机器人抓捕目标后基于任务相容性的消旋策略

针对双臂空间机器人抓捕自旋目标后的镇定操作,在考虑机器人系统输入约束的条件下,提出了一种基于任务相容性的消旋规划与控制方法。首先,给出空间机器人抓捕目标后的组合系统的动力学模型,作为规划与控制的基础。然后,根据动力学可操作度和任务相容性设计了目标的快速消旋策略,其期望加速度的方向和大小分别取作速度的反方向和机器人系统输入约束允许的最大值。最后,基于所推导的运动学和动力学模型,通过对目标和机械臂末端分别建立柔顺度等式,提出了一种跟踪期望运动轨迹同时对末端接触力进行调节的柔顺控制方法。通过双臂7自由度空间机器人消除目标自旋运动的仿真结果,验证了所提方法的有效性。     

Motion planning for tree climbing with inchworm‐like robots

This paper proposes a global path‐ and motion‐planning algorithm that enables inchworm‐like robots to navigate their way up tree branches. The intuitive climbing space representation method proposed here greatly simplifies the path‐planning problem. The dynamic programming algorithm can be used to identify the optimal path leading to the target position in the target direction according to the constraints and requirements specified. The planned path can be applied in any tree‐climbing robot that utilizes the nonenclosure gripping method. An efficient motion‐planning algorithm for continuum inchworm‐like robots is then developed to enable them to climb along the planned path with a high degree of accuracy. In comparison with the method proposed in our previous study, the method proposed herein significantly improves consistency between the planned path and the motions of the robot, and therefore makes it more practical to implement the motion‐planning algorithm in trees of different shapes. The paper also describes hardware experiments in which the proposed planning algorithm is applied to enable inchworm‐like robots to climb real trees, thus validating the proposed planning algorithm in practice. © 2012 Wiley Periodicals, Inc.     

基于强化学习的挖掘机时间最优轨迹规划

针对挖掘机的自主作业场景,提出基于强化学习的时间最优轨迹规划方法.首先,搭建仿真环境用于产生数据,以动臂、斗杆和铲斗关节的角度、角速度为状态观测变量,以各关节的角加速度值为动作信息,通过状态观测信息实现仿真环境与自主学习算法的交互;然后,设计以动臂、斗杆和铲斗关节运动是否超出允许范围、完成任务 总时间和目标相对距离为奖励函数对策略网络参数进行训练;最后,利用改进的近端策略优化算法(proximal policy optimization, PPO)实现挖掘机的时间最优轨迹规划.与此同时,与不同连续动作空间的强化学习算法进行对比,实验结果表明:所提出优化算法效率更高,收敛速度更快,作业轨迹更平滑,可有效避免各关节受到较大冲击,有助于挖掘机高效、平稳地作业.     

无人机自主目标识别与定位应用研究

面向无人机自主侦察任务中在线目标识别与定位需求,首先梳理了无人机侦察中目标识别领域的相关研究成果;然后,介绍了Faster RCNN目标识别算法的实现原理,并针对任务需求进行了改进;之后,介绍了图像拼接的相关算法并进一步提出了目标相对定位算法;最后,设计了完整的侦察试验流程对所设计自主目标识别与定位方法进行验证;结果表明,改进的目标检测网络能够达到83.3％的识别准确率和35帧/秒的识别速度,所提出的相对定位算法可以达到0.702 m的平均定位精度,能够满足侦察无人机在线目标识别与定位的任务需求.     

Coverage path planning with targetted viewpoint sampling for robotic free-form surface inspection

Surface metrology systems are increasingly used for inspecting dimensional quality in manufacturing. The gauge of these measurement systems is often mounted as an end-effector on robotic systems to exploit the robots’ high degrees of freedom to reposition the gauge to different viewpoints. With this repositioning flexibility, a planning methodology becomes necessary in order to carefully plan the viewpoints, as well as the optimal sequence and quickest path to move the gauge to each viewpoint. This paper investigates coverage path planning for robotic single-sided dimensional inspection of free-form surfaces. Reviewing existing feasible state-of-the-art methodologies to solve this problem led to identifying an unexplored opportunity to improve the coverage path planning, specifically by replacing random viewpoint sampling strategy. This study reveals that a non-random targetted viewpoint sampling strategy significantly contributes to solution quality of the resulting planned coverage path. By deploying optimisation during the viewpoint sampling, an optimal set of admissible viewpoints can be obtained, which consequently significantly shortens the cycle-time for the inspection task. Results that evaluate the proposed viewpoint sampling strategy for two industrial sheet metal parts, as well as a comparison with the state-of-the-art are presented. The results show up to 23.8% reduction in cycle-time for the inspection task when using targetted viewpoints sampling.     

凿岩机器人钻臂定位控制交叉精英反向粒子群算法

在利用粒子群优化算法(particle swarm optimization,PSO)进行凿岩机器人钻臂定位过程中,存在收敛速度慢和易于陷入局部最优解等问题.为此,提出一种交叉精英反向粒子群优化算法(crossover elite opposition-based particle swarm optimization,CEOPSO)并给出算法的流程.建立凿岩机器人钻臂运动学模型并对其逆向运动学进行求解.将交叉算子引入EOPSO中,采用自适应惯性权重和交叉概率参数控制技术,在维护粒子个体与最优解之间信息交换的基础上,增加粒子个体之间的信息交换,提高算法的全局搜索能力和钻臂定位效率.仿真结果表明,CEOPSO的平均位置误差和平均姿态误差均小于PSO和EOPSO算法,且迭代过程平稳,可以有效提高凿岩机器人钻臂的定位控制性能.     

Dynamic analysis and control of a stewart platform manipulator

The Stewart platform is a six-axis parallel robot manipulator with a force-to-weight ratio and positioning accuracy far exceeding that of a conventional serial-link arm. Its stiffness and accuracy approach that of a machine tool yet its workspace dexterity approaches that of a conventional manipulator. In this article, we study the dynamic equations of the Stewart platform manipulator. Our derivation is closed to that of Nguyen and Pooran because the dynamics are not explicitly given but are in a step-by-step algorithm. However, we give some insight into the structure and properties of these equations: We obtain compact expressions of some coefficients. These expressions should be interesting from a control point of view. A stiffness control scheme is designed for milling application. Some path-planning notions are discussed that take into account singularity positions and the required task. The objective is to make the milling station into a semiautonomous robotic tool needing some operator interaction but having some intelligence of its own. It should interface naturally with part delivery and other higher-level tasks.