动态环境中的多机器人协同搬运

在多机器人协同搬运过程中,针对传统的强化学习算法仅使用数值分析却忽略了推理环节的问题,将多机器人的独立强化学习与“信念-愿望-意向”（BDI）模型相结合,使得多机器人系统拥有了逻辑推理能力,并且,采用距离最近原则将离障碍物最近的机器人作为主机器人,并指挥从机器人运动,提出随多机器人系统位置及最近障碍物位置变化的评价函数,同时将其与基于强化学习的行为权重结合运用,在多机器人通过与环境不断交互中,使行为权重逐渐趋向最佳。仿真实验表明,该方法可行,能够成功实现协同搬运过程。     

自动化立体仓库搬运机器人精定位视觉系统

本文介绍一个搬运机器人的视觉系统.该系统是为机器人在具有较大相对位置偏差的货架中准确存取而研制的.系统由 CCD 摄象机获取货架图象,经过处理,给出精定位数据,从而引导机器人准确定位.     

双目-多运动副全向构型搬运机器人导引控制优化

控制与导引的协同问题在搬运机器人工作过程中经常受到关注。为此设计了一种双目-多运动副全向构型搬运机器人导引控制方法,对从协同导引控制展开全方位分析。结果表明：在直线路径上经强化学习优化后到达稳态值的收敛速度更快,有效降低稳态偏差。机器人控制优化后均方差及均值得到降低。协同路径跟踪实验纵向距离偏差结果意味着机器人间纵向距离的控制力在经强化学习后更平稳。协同导引控制有效性及可行性均可通过协同路径跟踪实验结果得到验证。该研究有助于提高搬运机器人协同工作效率,对后续的整理控制优化起到一定的理论支撑作用。     

基于Arduino的小型物品搬运机器人

搬运机器人作为一种典型的工业机器人,在交通运输、化工、食品加工、医疗等行业中具有广泛的应用.然而,现有的搬运机器人主要针对大型物品,没有充分考虑小型物品.针对该问题,该文设计了一款安卓手机App控制的小型搬运机器人.为能稳定抓取小型物品,该文参照人类手臂结构,通过大摆臂控制小摆臂,以实现灵活的操作;同时在小摆臂前端安装...     

双机器人协同控制研究综述

多机器人协同是未来机器人研究的一大热点,双机器人系统是其中的一个典型代表.针对目前双机器人协同系统的特性及常见应用,从动力学模型的建立、轨迹规划和协同控制等3方面介绍了双机器人协同系统的研究内容,分析各方面目前存在的技术漏洞和技术难点,指出未来发展的方向.     

多仓储机器人协同路径规划与作业避碰

针对多仓储移动机器人协同作业问题,提出了一种基于全局规划和局部调整的路径规划方法,以获得较短、无碰、避障的可行路径.在路径规划时根据当前节点到终点的距离和局部路径与起点至终点的欧氏路径的夹角设计新启发式函数,驱使机器人沿最短路行进;根据可选节点的数量提出避障规则,提高避障能力;依据路径长度对信息素进行比较更新,以精炼搜索空间、提高收敛性能,对蚁群算法加以改进寻找各自最优路径.在作业避碰时设计避碰规则有效解决仓储机器人间作业碰撞,找到最优或近优路径组合.实验结果表明了本方法的可行性、有效性.     

能耗约束优化工业机器人作业轨迹

工业机器人作业过程中普遍需要较高的能耗。基于量子行为和差分进化的改进蜻蜓算法,实现能耗约束下优化工业机器人避障作业轨迹。基于工业机器人五次B样条曲线矩阵式和动力学模型,构建能耗约束模型;进行仿真实验,利用改进蜻蜓算法求解能耗约束模型为适应度评价函数的工业机器人轨迹,对比改进蜻蜓算法与原始蜻蜓算法和基于指数函数步长的精英反向蜻蜓算法的优化结果,表明改进蜻蜓算法具有更优的性能。     

多无人艇协同围捕算法设计与仿真

为了实现对水面目标进行围捕的功能,提出了一种基于多无人艇的协同围捕算法。算法根据围捕无人艇的数量分配不同的目标相位,把整个围捕过程划分为编队前行、实施包围和靠近合拢三个阶段进行全局路径规划。算法设计简单实用,支持任意数量的围捕无人艇,路径节点数可调整,速度计算简单,具有防碰撞的特点。仿真实验验证了该算法的有效性。     

机器人轨迹跟踪自适应控制

本文提出一种新的自适应控制算法,用于补偿机器人动力学方程中的非线性项和消除关节间的耦合。这种简单有效的控制算法,保证了系统在一定的参数变化范围内具有渐近稳定性和良好的控制精度。     

无人机协同控制研究综述

无人机(UAV)协同控制是指一组UAV以机间通信为基础、群体智能为核心,合作分工完成某一共同任务的控制方式.UAV集群是拥有一定自主能力的大量UAV基于局部规则执行各项任务的多智能体系统,与单架UAV相比,UAV集群有着高效率、高灵活性和高可靠性等优点.针对近几年UAV协同控制技术的最新发展动态,首先,从民用和军事两个...     

PD-based trajectory tracking control in automatic cell injection system

Trajectory tracking technology has been the focus of industrial manipulatory applications for many years, and its research has been found in micromanipulation in bioengineering recently. In this paper, a hybrid vision and force control method is applied to the automatic cell injection. The three-dimensional cell injection process involves the trajectory tracking in free space and the force control in contact space. A PD plus feedforward compensation control method is applied to the trajectory tracking in 3D space. Further, a PD-based robust controller is introduced into trajectory tracking while the systemic uncertainty of the cell injection is additionally considered. Both of the two control methods are theoretically proved to be exponential convergent. Finally, the effectiveness of the proposed method is verified as compared with other control methods by its application to trajectory tracking problem.     

Efficient time-optimal two-corner trajectory planning algorithm for differential-driven wheeled mobile robots with bounded motor control inputs

We propose an efficient time-optimal trajectory planning algorithm for differential-driven wheeled mobile robots with bounded motor control inputs in the environment with cranked road where two corners with arbitrary angles exist. Based on dynamics for differential-driven wheeled mobile robots including actuating motors as well as on the bang–bang principle for time-optimality, we plan the time-optimal free path trajectory which unifies path planning and trajectory generation. Thus it improves total time significantly while handling obstacle avoidance. We divide our trajectory into three sections and then divide each section into an appropriate number of subsections to make five subsections in total. We introduce the concept of transition angle to solve the problem with formulating search loops efficiently. Numerical results are provided to validate the effectiveness of the proposed algorithm.     

基于视觉图像的全向移动机器人轨迹跟踪控制研究

机器人轨迹节点跟踪比较难,导致机器人实际轨迹偏离期望轨迹,所以设计基于视觉图像的全向移动机器人轨迹跟踪控制方法;构建全向移动机器人的运动学数学模型,以此确定机器人移动轨迹数学模型;以移动轨迹数学模型为基础,按照视觉图像划分标准对全向移动机器人运动图像的分割,通过分离目标节点的方式提取运动学特征参量,完成机器人轨迹节点跟踪处理;结合节点跟踪处理结果,将运动学不等式与误差向量作为机器人轨迹跟踪控制的约束条件,利用滑模变结构搭建轨迹跟踪控制模型,实现全向移动机器人轨迹跟踪控制;对比实验结果表明,所设计的方法应用后,全向移动机器人角速度曲线、线速度曲线与期望运动轨迹曲线之间的贴合程度均超过90%,满足全向移动机器人轨迹跟踪控制要求。     

基于轨迹跟踪车式移动机器人编队控制

针对车式移动机器人的运动学模型特点, 提出一种基于轨迹跟踪多机器人编队控制方法. 首先利用编队结构参数确定队形, 根据编队轨迹和相关参数生成虚拟机器人, 把编队控制转化为跟随机器人对虚拟机器人的轨迹跟踪; 然后运用反步法构造车式移动机器人轨迹跟踪系统的Lyapunov 函数, 通过使该函数负定, 得到跟随机器人的轨迹跟踪控制器; 最后在Microsoft robotics developer studio 4 (MRDS4) 中搭建3D 仿真平台, 设计了3 组实验, 所得结果表明了所提出方法的有效性.     

无人机三维航路自适应跟踪控制

针对无人机自动驾驶仪参数标称值偏离实际值情况下的航迹跟踪问题,提出一种无人机三维航路自适应跟踪导引律。首先在无人机自动驾驶仪参数无偏离的条件下,推导出能够跟踪三维航路的速度指令、航迹倾斜角指令和航迹方位角指令,并使用Lyapunov稳定性理论证明了跟踪系统全局渐进稳定;之后考虑自动驾驶仪参数标称值偏离实际值的情况,设计自适应算法在线估计自动驾驶仪参数,得到无人机三维航路自适应跟踪导引律。仿真实验表明所提出的自适应跟踪导引律能够使无人机在自动驾驶仪参数偏离条件下有效跟踪三维航迹。     

Global trajectory tracking control of VTOL-UAVs without linear velocity measurements

This paper deals with the position control of Vertical Take-Off and Landing (VTOL) Unmanned Aerial Vehicles (UAVs) without linear velocity measurements. We propose a multistage constructive procedure, exploiting the cascade property of the translational and rotational dynamics. More precisely, we consider the force as a virtual control input for the translational dynamics, from which we extract the required (desired) system attitude and thrust achieving the tracking objective. Thereafter, the control torque is designed to drive the actual attitude to the desired one. A nonlinear observer, as well as some instrumental auxiliary variables are used to obviate the need for the linear velocity. Global asymptotic stability of the overall closed loop system is achieved. Simulation results are provided to show the effectiveness of the proposed control scheme.     

Simultaneous dynamic optimization: A trajectory planning method for nonholonomic car-like robots

Trajectory planning in robotics refers to the process of finding a motion law that enables a robot to reach its terminal configuration, with some predefined requirements considered at the same time. This study focuses on planning the time-optimal trajectories for car-like robots. We formulate a dynamic optimization problem, where the kinematic principles are accurately described through differential equations and the constraints are strictly expressed using algebraic inequalities. The formulated dynamic optimization problem is then solved by an interior-point-method-based simultaneous approach. Compared with the prevailing methods in the field of trajectory planning, our proposed method can handle various user-specified requirements and different optimization objectives in a unified manner. Simulation results indicate that our proposal efficiently deals with different kinds of physical constraints, terminal conditions and collision-avoidance requirements that are imposed on the trajectory planning mission. Moreover, we utilize a Hamiltonian-based optimality index to evaluate how close an obtained solution is to being optimal.     

四旋翼无人飞行器的轨迹跟踪与滑模事件驱动控制

四旋翼飞行器作为一个典型的欠驱动的系统,具有强耦合、非线性等特性.针对飞行器外部干扰、和通信资源受限条件下的轨迹跟踪控制问题,进行滑模事件驱动控制方法的研究.首先,分析动力学特性,通过时间尺度分解方法将系统解耦成位置子系统和姿态子系统.其次,将位置子系统转化为严格反馈形式,设计反步滑模控制器,实现位置轨迹稳定跟踪;针对姿态子系统存在时变有界扰动及通信受限,设计滑模事件驱动控制律,在抑制干扰的同时实现对虚拟姿态跟踪指令的跟踪.根据Lyapunov分析方法证明了所设计控制器的稳定性,并通过理论分析证明闭环控制系统不会出现Zeno现象.最后,仿真结果验证了滑模事件驱动控制律在存在外部扰动和通信受限时四旋翼无人飞行器轨迹跟踪的鲁棒性.     

A survey on tracking control of unmanned underwater vehicles: Experiments-based approach

This paper aims to provide a review of the conceptual design and theoretical framework of the main control schemes proposed in the literature for unmanned underwater vehicles (UUVs). Additionally, the objective of the paper is not only to present an overview of the recent control architectures validated on UUVs but also to give detailed experimental-based comparative studies of the proposed control schemes. To this end, the main control schemes, including proportional–integral–derivative (PID) based, sliding mode control (SMC) based, adaptive based, observation-based, model predictive control (MPC) based, combined control techniques, are revisited in order to consolidate the principal efforts made in the last two decades by the automatic control community in the field. Besides implementing some key tracking control schemes from the classification mentioned above on Leonard UUV, several real-time experimental scenarios are tested, under different operating conditions, to evaluate and compare the efficiency of the selected tracking control schemes. Furthermore, we point out potential investigation gaps and future research trends at the end of this survey.