基于误差补偿的移动式双臂协作机器人自适应协同装配均衡控制方法

为了提高移动式双臂协作机器人的自适应协同控制能力,提出基于反馈调节均衡误差补偿的移动式双臂协作机器人自适应协同装配均衡性控制技术。构建移动式双臂协作机器人控制约束参数和对象模型,采用空间规划和负荷均衡调节方法,实现对移动式双臂协作机器人的自适应参数融合和控制量优化辨识,通过随机负荷误差补偿的方法构建移动式双臂协作机器人自适协同装配过程中的均衡参数集,结合模糊度检测和自适应跟踪补偿方法,构建移动式双臂协作机器人的自适应均衡控制模型,根据参数寻优结果,实现对移动式双臂协作机器人自适应协同装配过程中的反馈调节均衡误差补偿,提高装配的稳定性和可靠性。仿真结果表明,采用该方法进行移动式双臂协作机器人自适应协同装配控制的输出均衡性较好,误差补偿能力较强,提高了机器人控制的稳定性和鲁棒性。     

桌面机械手双臂协作试验研究

针对一些工业机器人在较小的工作空间,且对机器人精度要求不高的应用场合,设计使用小尺寸和低成本的桌面机械手代替工业级机械手进行作业任务,同时用两台桌面机械手组成的双臂机械手进行协作完成任务.以桌面机械手双臂为研究对象,采用D-H法对机械手双臂进行建模并进行运动学分析.在运动学基础上结合蒙特—卡罗法求解双臂工作空间,同时对...     

基于引力自适应步长RRT的双臂机器人协同路径规划

快速扩展随机树（RRT）方法的步长确定过分依赖于程序调试,而且固定的步长会导致碰撞检测失效问题．针对此问题,本文提出一种适用于双臂机器人协同路径规划的引力自适应步长RRT．首先,通过建立构型空间与工作空间的步长范数不等式,对双臂机器人在工作空间中所产生的步长进行约束,进而确保实现有效的碰撞检测;然后,提出随机树被动生长方法,在保证双臂机器人协同运动的基础上,降低规划空间的维度．最后,在随机树的节点处引入引力函数,加快算法的融合速度．仿真结果表明,引力自适应步长RRT方法可对工作空间中的步长进行有效约束,确保算法碰撞检测的有效性．在无碰撞的前提下,引力自适应步长RRT方法相比于其他算法减少了迭代次数,降低了运行时间并缩短了路径长度．将所提算法应用于双臂机器人的样机实验,结果表明双臂机器人可在保持位置协同的前提下,完成避障运动,验证了算法的可行性．     

基于参数与非参数模型结合的双臂机器人协作定位精度提升方法

双臂协作机器人系统具有效率高、负载大、协同能力强等优点,但双臂作业性能及质量不但受单臂定位精度的影响,而且受双臂协作定位精度的影响,因此,本文提出了一种基于参数与非参数模型相结合的运动学标定方法。首先,基于MDH(modified Denavit-Hartenberg)方法建立机器人运动学模型和参数误差模型,去除模型中的耦合参数并基于迭代最小二乘法辨识几何参数误差;其次,针对传统的非几何误差补偿方法只能在标定坐标系建立关节位置与末端位置误差之间的映射关系的问题,提出一种改进的非几何误差补偿方法补偿机器人本体非几何误差;再次,基于距离误差辨识双臂基坐标系转换矩阵的参数,补偿双臂几何误差与非几何误差;最后,通过实验验证方法的正确性和有效性。结果表明所提出方法将UR10和UR5机器人的平均定位误差减小至0.170 9 mm和0.050 9 mm。双臂平均协作定位误差减小至0.167 6 mm,与基于参数模型的方法相比协作定位精度提升了27.7%,验证了该方法的优越性。     

基于HMS的双臂机器人运动学协调约束模型研究

论文主要研究了双臂机器人的协调运动。建立双臂机器人协调运动模型,根据双臂机器人进行实际任务时的相对位置控制关系,建立一种基于两机械臂协作过程中相对运动的约束协调算法模型,通过和声搜索算法,期望能够根据所得运动最优解增进双臂协调运动过程中的平稳性,并且能够减小仿真过程中的相对误差,保证双臂机器人在进行任务的过程中双臂之间的约束关系。     

面向实时自避碰的双臂机器人力矩控制策略

为解决双臂机器人运动过程中的自碰撞问题，提出了一种面向实时自避碰的双臂机器人力矩控制策略。利用机械臂正向运动学构建双臂机器人动态骨架包围盒，用于简化计算关节间最小距离；根据机械臂关节空间阻抗控制规则，设计了基于关节间距离的力矩控制算法，将运动中各关节间距离转换为避碰力矩，并将避碰力矩和其他任务的期望力矩相加，从而得到控制双臂机器人运动的实际力矩。实验表明：当双臂机器人的设定杆件相互靠近且达到避碰距离时，本研究所提出的自避碰策略能够及时对机器人的运动关节产生一组平滑的避碰力矩，避免了机器人自身发生碰撞，验证了所提算法的有效性及实用性。     

中医按摩机器人双臂推拿过程的避碰控制

讨论了中医按摩机器人的双臂协调运动控制问题.根据机械臂的结构特点,将空间避碰问题转化为平面内的避碰问题,对按摩机器人双臂推拿过程中可能发生的碰撞情况进行了分析.利用平面几何方法,对机器人双臂协调推拿过程进行了避碰规划,设计出一套双臂协调运动控制策略.利用MATLAB对双臂的避碰情况进行了运动学仿真,仿真结果表明本文中设计的方法可以有效的实现双臂在推拿过程中的协调运动.     

基于运动性能分析的双臂冗余度机器人协调运动研究

为了提高双臂冗余度机器人在其交互工作空间中的协调运动能力,以ABB YuMi为例,提出了一种计算简便并且能够有效反映双臂协调运动灵活性的性能指标。利用D-H法建立了YuMi机器人的运动学模型,分析了双臂可操作度的分布情况,分别研究了两种协调运动方式的运动学约束关系以及相应的运动控制规律,基于灵活性分析构建了双臂协调装配电机转子与轴承以及字母绘制的任务,通过仿真和实验验证了本文双臂可操作度指标的有效性及协调运动规划方法的正确性。     

Motoman先进人形工业机器人介绍

本文介绍了Motoman双臂人形机器人研究背后的创新思维,并研究了它的技术设计以及工业用途,提出了多臂协作机器人的总体优势。     

双臂空间机器人协调操作运动控制仿真系统的设计与实现

阐述了双臂自由飞行空间机器人闭链式协调操作运动控制实验平台的建立方法。将VC 6.0、OpenGL、Matlab和Matcom四种软件融合起来,搭建FFSR(自由飞行空间机器人)系统实验平台;通过运动控制算法描述了机器人双臂协调操作目标物的动态特性,给出了机器人本体中心的位置姿态和转角的变化曲线,验证了该运动控制算法的正确性,以及编程效率的优越性。     

求解并联机床工作空间的算法分析和研究

本文针对三自由度并联机床的机构进行了分析,并求出了其位置逆解。在此基础上对求解其工作空间所采用的算法进行了研究和分析,重点给出了边界搜索法的设计方法,并进行了相关算法的分析。结果表明,在机构没有空洞的情况下,边界搜索法是一种理想的求解工作空间的算法     

基于ROS的协作机器人控制系统

为了实现协作机器人的控制,对协作机器人进行了控制系统研究,在保证系统鲁棒性和实时性的前提下,提出了在PC机上,构建基于Ubuntu系统下结合ROS,利用CAN通讯的方式,搭建协作机器人的控制系统.最后通过仿真实验和实体机器人控制实验,验证协作机器人控制系统应用效果.实验结果表明,该协作机器人控制系统具备控制协作机器人进行路径规划的基本工作能力,能够很好的建立上下位机的通讯,进行协作机器人控制.同时本控制系统具有模块化、可移植性高、框架清晰、低延时等特点.     

Virtual target tracking of mobile robot and its application to formation control

A virtual target tracking approach is proposed for kinematic control of mobile robot. In the controller, linear and angular velocity inputs are generated by using the local data of robot position and orientation along with the estimated velocity of target object. Applying the proposed approach to a cooperative robot group with arbitrary number of multiple mobile robots, it is possible to create various robot formations for cooperative navigation and tracking of moving object. The developed controller is shown to be stable and convergent through theoretical proof and a series of experiments.     

A humanoid robot that pretends to listen to route guidance from a human

This paper reports the findings for a humanoid robot that expresses its listening attitude and understanding to humans by effectively using its body properties in a route guidance situation. A human teaches a route to the robot, and the developed robot behaves similar to a human listener by utilizing both temporal and spatial cooperative behaviors to demonstrate that it is indeed listening to its human counterpart. The robot's software consists of many communicative units and rules for selecting appropriate communicative units. A communicative unit realizes a particular cooperative behavior such as eye-contact and nodding, found through previous research in HRI. The rules for selecting communicative units were retrieved through our preliminary experiments with a WOZ method. An experiment was conducted to verify the effectiveness of the robot, with the results revealing that a robot displaying cooperative behavior received the highest subjective evaluation, which is rather similar to a human listener. A detailed analysis showed that this evaluation was mainly due to body movements as well as utterances. On the other hand, subjects' utterance to the robot was encouraged by the robot's utterances but not by its body movements.     

Cooperative embodied communication emerged by interactive humanoid robots

Research on humanoid robots has produced various uses for their body properties in communication. In particular, mutual relationships of body movements between a robot and a human are considered to be important for smooth and natural communication, as they are in human–human communication. We have developed a semi-autonomous humanoid robot system that is capable of cooperative body movements with humans using environment-based sensors and switching communicative units. Concretely, this system realizes natural communication by using typical behaviors such as: “nodding,” “eye-contact,” “face-to-face,” etc. It is important to note that the robot parts are NOT operated directly; only the communicative units in the robot system are switched. We conducted an experiment using the mentioned robot system and verified the importance of cooperative behaviors in a route-guidance situation where a human gives directions to the robot. The task requires a human participant (called the “speaker”) to teach a route to a “hearer” that is (1) a human, (2) a developed robot that performs cooperative movements, and (3) a robot that does not move at all. This experiment is subjectively evaluated through a questionnaire and an analysis of body movements using three-dimensional data from a motion capture system. The results indicate that the cooperative body movements greatly enhance the emotional impressions of human speakers in a route-guidance situation. We believe these results will allow us to develop interactive humanoid robots that sociably communicate with humans.     

Learning cooperative grasping with the graph representation of a state-action space

In this paper we present a method for two robot manipulators to learn cooperative tasks. If a single robot is unable to grasp an object in a certain orientation, it can only continue with the help of other robots. The grasping can be realized by a sequence of cooperative operations that re-orient the object. Several sequences are needed to handle the different situations in which an object is not graspable for the robot. It is shown that a distributed learning method based on a Markov decision process is able to learn the sequences for the involved robots, a master robot that needs to grasp and a helping robot that supports him with the re-orientation. A novel state-action graph is used to store the reinforcement values of the learning process. Further an example of aggregate assembly shows the generality of this approach.     

Synchronized adaptive control for coordinating manipulators with time‐varying actuator constraint and uncertain dynamics

This paper addresses the control issue for cooperative visual servoing manipulators on strongly connected graph with communication delays, in which case that the uncertain robot dynamics and kinematics, uncalibrated camera model, and actuator constraint are simultaneously considered. An adaptive cooperative image‐based approach is established to overcome the control difficulty arising from nonlinear coupling between visual model and robot agents. To estimate the coupled camera‐robot parameters, a novel adaptive strategy is developed and its superiority mainly lies in the containment of both individual image‐space errors and the synchronous errors among networked robots; thus, the cooperative performance is significantly strengthened. Moreover, the proposed cooperative controller with a Nussbaum‐type gain is implemented to both globally stabilize the closed‐loop systems and realize the synchronization control objective under the existence of unknown and time‐varying actuator constraint. Finally, simulations are carried out to validate the developed approach.     

Cooperative localization and evaluation of small-scaled spherical underwater robots

With the goal of supporting localization requirements of our spherical underwater robots, such as multi robot cooperation and intelligent biological surveillance, a cooperative localization system of multi robot was designed and implemented in this study. Given the restrictions presented by the underwater environment and the small-sized spherical robot, an time of flight camera and microelectro mechanical systems (MEMS) sensor information fusion algorithm using coordinate normalization transfer models were adopted to construct the proposed system. To handle the problem of short location distance, limited range under fixed view of camera in the underwater environment, a MEMS inertial sensor was used to obtain the attitude information of robot and expanding the range of underwater visual positioning, the transmission of positioning information could implement through the normalization of absolute coordinate, then the positioning distance increased and realized the localization of multi robot system. Given the environmental disturbances in practical underwater scenarios, the Kalman filter model was used to minimizing the systematic positioning error. Based on the theoretical analysis and calculation, we describe experiments in underwater to evaluate the performance of cooperative localization. The experimental results confirmed the validity of the multi robot cooperative localization system proposed in this paper, and the distance of cooperative localization system proposed in this paper is larger than the visual positioning system we have developed previously.

     

无人仓多搬运机器人协同作业轨迹自动控制研究

由于无人仓多搬运机器人协同作业线路较为复杂,导致协同作业轨迹控制难度增加,为了保证多搬运机器人能够按照规划路线执行搬运作业,提出了无人仓多搬运机器人协同作业轨迹自动控制方法;采用栅格图建模法,结合无人仓内货架的实际分布情况,建立无人仓环境场景;从组成结构、运动学以及动力学3个方面,构建搬运机器人的数学模型;遵循就近原则分配多机器人搬运任务,规划多搬运机器人的协同作业轨迹,根据多搬运机器人实时位姿的自动检测结果计算控制量,利用作业轨迹自动控制器的安装与运行,完成无人仓多搬运机器人协同作业轨迹的自动控制任务;实验结果表明,在该方法应用后,多搬运机器人在无人仓中的作业轨迹与规划轨迹基本相同,计算得出的平均位置控制误差和姿态角控制误差分别为2.27 cm和0.05°,搬运机器人的碰撞次数能被控制在规定范围内,实际应用效果好。     

一种改进的多机器人协作实时FastSLAM算法

针对FastSLAM1.0中机器人缺乏自身定位测量修正引起的累积误差和FastSLAM2.0引入测量修正引起算法复杂度增加的问题,提出一种改进的基于辅助测量的多机器人协作实时FastSLAM算法,使用双机器人协同工作,领头机器人负责完成同时定位与地图构建任务,辅助机器人通过静态相对位置测量为领头机器人提供实时定位测量修正.该辅助测量方法不仅为SLAM任务执行机器人提供较准确的定位测量值,同时也避免了FastSLAM2.0算法中额外的算法复杂度问题.实验结果表明算法既可以获得较高的精度,而且方便可行,具有较高实用价值.