The kinematics modeling based on Spinor theory for CT-guided hybrid robot

This paper focused on a simplified method for solving the hybrid robot kinematics in CT-guided （computerized tomography, CT） surgery. By position constraint introduced, the hybrid robot can be transformed as a redundant serial 7-DOF robot. The forward displacement calculation was developed based on the product-of-exponential formula （POE）. Because of the kinematics complexity of the hybrid and redundant robot, the combination technique of Ulrich two-step iteration method and paul variables detachment method （UTI-PVD） was introduced to fulfill the inverse kinematics of redundant robot, the novelty of which lay in the flexibility of various robots structures and in high calculation efficiency for realtime control. The process of solving the inverse displacement was analyzed. The UTI-PVD method can be applicable to kinematics of many robots, especially for redundant robots with more than 6DOF. The kinematics simulation was provided, and robot dexterity analysis was presented. The results indicated that the hybrid robot could implement the minimally invasive CT-guided surgery.

Dynamics of 3-DOF Hybrid Robot Manipulator

This paper introduces a 3-dof hybrid robotic manipulator which is constructed by combining a parallel mechanism and a pantograph to increase stiffness as well as workspace. And by analyzing its kinematics and dynamics with Lagrange’s method, the dynamic model is obtained which is essential for feed-forward control of the manipulator. An explicit solution is given out. Finally, a simulation test is carried out on computers.

An iterative learning method for realizing accurate dynamic feedforward control of an industrial hybrid robot

Feedforward control based on an accurate dynamic model is an effective approach to reduce the dynamic effect of the robot and improve its performance. However, due to the complicated work environment with considerable uncertainty, it is difficult to obtain a high-precision dynamic model of the robot, which severely deteriorates the achievable control performance. This paper proposes an iterative learning method to accurately design the industrial feedforward controller and compensate for the external uncertain dynamic load of the robot. Based on a standard dynamic model, a complete linear feedforward controller is presented.An iterative design strategy is given to iteratively update the feedforward controller by combining the Moore-Penrose Inverse and the PID learning rate. Experiments are carried out on a 5-DOF industrial hybrid robot to validate the effectiveness of the proposed iterative learning method. The experiment results illustrate that the industrial feedforward controller can rapidly converge to the optimal controller and significantly improve the servo performance by using the proposed method. This paper provides an effective method for applying iterative learning control to an unopened industrial control system. It is very useful for the practical control of hybrid robots in industrial field.

Analysis on the crossing obstacle of wheel-track hybrid mobile robot

A novel wheel-track hybrid mobile robot with many movement patterns is designed.According to different environments,it can switch between the pure wheel pattern and the pure track one.According to a homogeneous coordinate transformation matrix,gravity stability and its obstacle performance are analyzed.Its gravity equation and climbing obstacle conditions are established.Experimental results show that this hybrid mobile robot could fully possess the advantages of both the wheel and the track mechanisms and achieve a good obstacle climbing capability.

A Closed-Loop Dynamic Controller for Active Vibration Isolation Working on A Parallel Wheel-Legged Robot

Serving the Stewart mechanism as a wheel-legged structure,the most outstanding superiority of the proposed wheel-legged hybrid robot(WLHR)is the active vibration isolation function during rolling on rugged terrain.However,it is difficult to obtain its precise dynamic model,because of the nonlinearity and uncertainty of the heavy robot.This paper presents a dynamic control framework with a decentralized structure for single wheel-leg,position tracking based on model predictive control(MPC)and adaptive impedance module from inside to outside.Through the Newton-Euler dynamic model of the Stewart mechanism,the controller first creates a predictive model by combining Newton-Raphson iteration of forward kinematic and inverse kinematic calculation of Stewart.The actuating force naturally enables each strut to stretch and retract,thereby realizing six degrees-of-freedom(6-DOFs)position-tracking for Stewart wheel-leg.The adaptive impedance control in the outermost loop adjusts environmental impedance parameters by current position and force feedback of wheel-leg along Z-axis.This adjustment allows the robot to adequately control the desired support force tracking,isolating the robot body from vibration that is generated from unknown terrain.The availability of the proposed control methodology on a physical prototype is demonstrated by tracking a Bezier curve and active vibration isolation while the robot is rolling on decelerate strips.By comparing the proportional and integral(PI)and constant impedance controllers,better performance of the proposed algorithm was operated and evaluated through displacement and force sensors internally-installed in each cylinder,as well as an inertial measurement unit(IMU)mounted on the robot body.The proposed algorithm structure significantly enhances the control accuracy and vibration isolation capacity of parallel wheel-legged robot.

基于改进Hybrid A^(*)算法的阿克曼移动机器人路径规划

针对移动机器人路径规划的效率和所规划路径的安全性问题,基于阿克曼六轮转向模型,提出了一种基于改进Hybrid A^(*)算法的路径规划方法。通过改进Hybrid A^(*)算法中的启发式函数,引入距离惩罚函数,减少了节点搜索数量;通过构建安全走廊,引导移动机器人尽可能远离障碍物;在代价函数中加入了节点向前、换向和向后扩展的惩罚项,确保所规划路径的可执行性与安全性。通过仿真表明,基于改进Hybrid A^(*)算法的路径规划方法适用于阿克曼六轮移动机器人,提高了路径规划的效率,规划的路径更具安全保障。

Hybrid force control of astronaut rehabilitative training robot under active loading mode

In order to mitigate the effects of space adaptation syndrome(SAS) and improve the training efficiency of the astronauts, a novel astronaut rehabilitative training robot(ART) was proposed. ART can help the astronauts to carry out the bench press training in the microgravity environment. Firstly, a dynamic model of cable driven unit(CDU) was established whose accuracy was verified through the model identification. Secondly, to improve the accuracy and the speed of the active loading, an active loading hybrid force controller was proposed on the basis of the dynamic model of the CDU. Finally, the actual effect of the hybrid force controller was tested by simulations and experiments. The results suggest that the hybrid force controller can significantly improve the precision and the dynamic performance of the active loading with the maximum phase lag of the active loading being 9° and the maximum amplitude error being 2% at the frequency range of 10 Hz. The controller can meet the design requirements.

A Study on Development of a Hybrid Aerial/Terrestrial Robot System for Avoiding Ground Obstacles by Flight

To date, many studies related to robots have been performed around the world. Many of these studies have assumed operation at locations where entry is difficult, such as disaster sites, and have focused on various terrestrial robots, such as snake-like, humanoid, spider-type, and wheeled units. Another area of active research in recent years has been aerial robots with small helicopters for operation indoors and outdoors. However,less research has been performed on robots that operate both on the ground and in the air. Accordingly, in this paper, we propose a hybrid aerial/terrestrial robot system. The proposed robot system was developed by equipping a quadcopter with a mechanism for ground movement. It does not use power dedicated to ground movement, and instead uses the flight mechanism of the quadcopter to achieve ground movement as well. Furthermore, we addressed the issue of obstacle avoidance as part of studies on autonomous control. Thus, we found that autonomous control of ground movement and flight was possible for the hybrid aerial/terrestrial robot system, as was autonomous obstacle avoidance by flight when an obstacle appeared during ground movement.

Application of Artificial Neural Network in Robotic Hybrid Position/Force Control

A hybrid position/force controller is designed for the joint 2 and the joint 3 of thePUMA 560 robot.The hybrid controller includes a multilayered neural network,which canidentify the dynamics of the contacted environment and can optimize the parameters of PIDcontroller.The experimental results show that after having been trained,the robot has sta-ble response to the training patterns and strong adaptive ability to the situation between thepatterns.

A Sensing and Robot Navigation of Hybrid Sensor Network

Traditional sensor network and robot navigation are based on the map of detecting fields available in advance. The optimal algorithms are explored to solve the energy saving, shortest path problems, etc. However, in practical environment, there are many fields, whose map is difficult to get, and need to detect. This paper explores a kind of ad-hoc navigation algorithm based on the hybrid sensor network without the prior map. The system of navigation is composed of static nodes and mobile nodes. The static nodes monitor events occurring and broadcast. In the system, a kind of cluster broadcast method is adopted to determine the robot localization. The mobile nodes detect the adversary or dangerous fields and broadcast warning message. Robot gets the message and follows ad-hoc routine to arrive the events occurring place. In the whole process, energy saving has taken into account. The algorithms of nodes and robot are given in this paper. The simulate and practical results are available as well.

Collision avoidance for a mobile robot based on radial basis function hybrid force control technique

Collision avoidance is always difficult in the planning path for a mobile robot. In this paper, the virtual force field between a mobile robot and an obstacle is formed and regulated to maintain a desired distance by hybrid force control algorithm. Since uncertainties from robot dynamics and obstacle degrade the performance of a collision avoidance task, intelligent control is used to compensate for the uncertainties. A radial basis function （RBF） neural network is used to regulate the force field of an accurate distance between a robot and an obstacle in this paper and then simulation studies are conducted to confirm that the proposed algorithm is effective.

香蕉采摘与吊运作业机器人运动与动力性能分析

由于香蕉果串的结果高度和果形尺寸较大,且采摘过程极易发生损伤,给其采摘带来极高难度,目前仍停留在比较落后的人工采摘方式上,劳动强度大。为此,提出了一种香蕉采摘与吊运作业机器人,可将香蕉果柄的切割、夹持和香蕉果串的吊放作业整体性完成,其机械系统主要由伺服连杆机械臂、夹持与切割末端执行器和液压履带行走动力单元等部分组成。工作时,末端执行器夹持与切割香蕉果柄的直径范围为40~150mm,液压履带车行走的最大行走速度为1.07m/s。通过基于ADAMS的机械系统运动和动力学仿真分析获得了伺服连杆机械臂的作业范围,以香蕉按照宽窄行宜机化种植模式为基础,对接近实际情况的伺服驱动作业流程进行了仿真研究,验证了各伺服电机的驱动能力。

Hybrid Visual Servoing Control for Robotic Arc Welding Based on Structured Light Vision

A novel hybrid visual servoing control method based on structured light vision is pro-posed for robotic arc welding with a general six degrees of freedom robot. It consists of a positioncontrol inner-loop in Cartesian space and two outer-loops. One is position-based visual control inCartesian space for moving in the direction of weld seam, i.e., weld seam tracking, another is image-based visual control in image space for adjustment to eliminate the errors in the process of tracking.A new Jacobian matrix from image space of the feature point on structured light stripe to Cartesianspace is provided for dierential movement of the end-e?ector. The control system model is simplifiedand its stability is discussed. An experiment of arc welding protected by gas CO2 for verifying iswell conducted.

基于双混联机器人协同运动控制的薄壁件镜像铣削研究

为提高薄壁件镜像铣削过程中的加工质量,本文提出一种针对双混联机器人镜像铣削的协同运动控制策略。首先,结合机器人运动控制特点,研发出一种双CPU主从控制架构的开放式数控系统,以实现人机交互和运动控制;然后,为实现双机协同运动并提高薄壁件加工质量,在数控系统中集成了4大关键技术,分别是双机器人的镜像路径生成、同步速度规划、协同运动学和运动误差实时补偿;最后,基于自主开发的集成式镜像铣削数控系统,开展了单点和多点支撑、双机协同与非协同加工的平面薄壁件槽铣削试验,多点支撑的平面铣削试验,大曲率路径高速协同运动试验与曲面薄壁件槽铣削加工试验。试验结果表明,提出的协同运动控制策略能够保证双机器人具有较高的同步位置精度。此外,多点支撑方式在保证薄壁件铣削壁厚的同时,还可提高工件铣削的颤振稳定性。

对称悬架混联轮腿机器人结构设计与参数优化

为了实现机器人在地下空间低能耗的灵活运动,文中设计了一种对称悬架混联轮腿机器人,并针对其腿部参数优化问题,提出了一种基于沙猫群算法的性能均衡优化方法(简称均衡优化方法)。结合对称四边形机构与悬架系统,设计了一种对称悬架混联式轮腿结构,并建立其运动学和动力学模型,分析了腿部杆长对单轮腿运动空间和灵活性指标的影响,预优化确定了腿部初始杆长均为0.3 m。在满足轮腿越障规划空间及高灵活性的基础上,为了实现低能耗,建立了轮腿性能均衡优化评价指标,采用均衡优化方法对腿部杆长进行了优化研究。数值计算结果表明:大腿和小腿杆长最优值分别为0.23 m和0.3 m,该轮腿运动能耗为23.18 J,运动空间为0.1322 m2,灵活性指标变化范围为(0.2,1)。优化后灵活性保持不变,运动空间减小了24.54%,能耗降低了22.60%,验证了该方法合理有效,为轮腿机器人的设计与优化提供了一种新的思路。

全状态约束下长行程混联机器人投影迭代鲁棒控制算法

针对全状态约束下的长行程混联机器人系统鲁棒性较差提出了基于自适应学习神经网络和等效误差函数的投影迭代鲁棒控制算法。基于自适应学习神经网络逼近未知的非线性项,提出投影迭代鲁棒控制算法,更新网络权值并估计逼近误差和随机外部扰动的未知上界;构造用于抵消初始时刻随机变化扩展误差的时变边界层,设计基于时变边界层和扩展误差的等效误差函数作为迭代控制器的主要控制变量以克服随机初始误差满足相同初始条件;在控制器设计中引入正切型障碍Lyapunov函数,确保系统状态在预定范围内。仿真实验结果证明了该方法的有效性,可在全状态约束下实现高精度强鲁棒性的轨迹跟踪。

基于改进HybridA^(*)的非完整约束机器人路径规划算法研究

为了实现单舵轮AGV在物流场景下的精准自主导航,针对基于HybridA*算法搜索的路径容易贴近障碍物的缺陷和算法在路径平滑后可能与障碍物冲突的问题,本文提出一种基于改进HybridA*的非完整约束轮式移动机器人路径规划方法。对于路径搜索部分,将距离场地图引入启发式函数,以提高搜索效率,并保持搜索路径远离障碍物;对于路径平滑部分,将优化问题转化为二次规划问题,通过边界约束保证避障效果。在ROS平台上仿真实验的结果表明,该路径规划方法可有效用于非完整约束系统,为单舵轮AGV自主导航的准确运动奠定了路径智能规划的基础。

基于改进运动原语生成的陆空两栖机器人Kinodynamic A^(*)算法

针对Kinodynamic A^(*)算法采用统一的运动原语生成,在陆空两栖机器人上应用时存在机动性无法充分发挥等问题,提出了基于改进运动原语生成的陆空两栖机器人Kinodynamic A^(*)算法。该算法从考虑陆、空模态运动能力差异出发,通过以下三个方法改进陆空两栖机器人Kinodynamic A^(*)算法性能。首先是基于动力边界决定状态空间加速度输入,差异化生成陆、空模态运动原语;其次是基于动力学约束剪枝,确保运动原语不超过速度边界;最后是构造轨迹优化代价函数优化轨迹平顺性、安全性及机动性。在仿真场景下的结果表明,所改进的算法在将空中平均速度提高了54.1%,平均路径总时间降低6.7 s,路径总代价降低22.00%,且算法运行时间降低0.069 s,充分发挥陆空两栖机器人上的强机动能力与高续航能力。

无人化仓库下异构机器人混合任务分配研究

在具有若干个障碍区的码头无人化仓库中,为解决异构机器人系统对混合任务的有效分配问题,文中提出一种模糊聚类融合的扩展一致性束算法。在采用模糊聚类划分任务子区域和利用时间窗设置混合任务执行顺序的基础上,提出机器人分组资源配置策略,以任务分配收益最大、运行时间最短为目标,建立异构机器人系统任务分配的数学模型,通过扩展一致性束算法,在各个子区域内完成任务分配。结果表明:扩展一致性束算法缩短了任务分配时间,得到各子区域内机器人的执行任务序列并且每架机器人所分配到的任务数保持均衡。

基于多目标均衡优化的2PRU&1PRS-XY型混联机器人尺度设计方法

面向复杂结构件机器人加工装备设计需求,提出一种2PRU&1PRS-XY型混联机器人。为将该混联机器人应用于高性能机械加工任务,在其工作空间、运动/力传递性以及灵巧度分析的基础上,定义了用于工作全域性能评价的传递稳定性指标与精度差异性指标,提出了一种基于多目标均衡优化思想的尺度设计方法。该方法采用标准化方法简化多参数设计空间,应用响应面法与主成分分析法提高优化求解效率,结合主客观组合赋权法与基于TOPSIS的Pareto前沿法实现多指标综合性能评分。运用所提方法,得到了4种兼顾优化求解效率和多目标均衡优化的尺度参数设计方案,实现了2PRU&1PRS-XY型混联机器人主要尺度参数的优化设计,为设计者提供了具有不同工程设计倾向的多目标均衡决策参考。