CBF-Based Distributed Model Predictive Control for Safe Formation of Autonomous Mobile Robots

A distributed model predictive control(DMPC)method based on robust control barrier function(RCBF)is developed to achieve the safe formation target of multi-autonomous mobile robot systems in an uncertain disturbed environment.The first step is to analyze the safety requirements of the system during safe formation and categorize them into collision avoidance and distance connectivity maintenance.RCBF constraints are designed based on collision avoidance and connectivity maintenance requirements,and security constraints are achieved through a combination.Then,the specified safety constraints are integrated with the objective of forming a multi-autonomous mobile robot formation.To ensure safe control,the optimization problem is integrated with the DMPC method.Finally,the RCBF-DMPC algorithm is proposed to ensure iterative feasibility and stability while meeting the constraints and expected objectives.Simulation experiments illustrate that the designed algorithm can achieve cooperative formation and ensure system security.

Predictive Control for Visual Servo Stabilization of Nonholonomic Mobile Robots

活动机器人获得了的 nonholonomic 的视觉伺服稳定广泛的注意。当前，这个问题的解决方案不管多么不认为可见性限制和致动器是限制，因此设计控制器是困难的在实际申请认识到令人满意的性能。在这份报纸，为一个活动机器人的视觉伺服稳定的一个预兆的控制器被介绍。第一，利用产生速度的命令的一个运动学的预兆的稳定控制器被介绍。然后，来临以便 asymptotically 做活动机器人的实际速度到需要的，一个动态预兆的控制器被设计。建议预兆的控制器能容易处理限制。最后，几模拟被执行，并且结果说明建议控制计划是有效的解决视觉伺服稳定问题。

Application of Linear Model Predictive Control and Input-Output Linearization to Constrained Control of 3D Cable Robots

Cable robots are structurally the same as parallel robots but with the basic difference that cables can only pull the platform and cannot push it. This feature makes control of cable robots a lot more challenging compared to parallel robots. This paper introduces a controller for cable robots under force constraint. The controller is based on input-output linearization and linear model predictive control. Performance of input-output linearizing (IOL) controllers suffers due to constraints on input and output variables. This problem is successfully tackled by augmenting IOL controllers with linear model predictive controller (LMPC). The effecttiveness of the proposed method is illustrated by numerical simulation.

Dynamic modeling and simulation for nonholonomic welding mobile robot

Based on the Newton-Euler method, the dynamic behaviors of the left and right driving wheels and the robot body for the welding mobile robot were derived. In order to realize the combination control of body turning and slider adjustment, the dynamic behaviors of sliders were also investigated. As a result, a systematic and complete dynamic model for the welding mobile robot was constructed. In order to verify the effectiveness of the above model, a sliding mode tracking control method was proposed and simulated, the lateral error stabilizes between -0.2 mm and ＋0.2 mm, and the total distance of travel for the slider is consistently within 4-2 ram. The simulation results verify the effectiveness of the established dynamic model and also show that the seam tracking controller based on the dynamic model has excellent performance in terms of stability and robustness. Furthermore, the model is found to be very suitable for practical applications of the welding mobile robot.

Formation Control and Obstacle Avoidance for Multiple Mobile Robots

这篇论文为一组 nonholonomic 考虑形成控制和障碍回避的问题活动机器人。根据非最优的模型预兆的控制，二个控制算法被建议。当解决费用在工作的最佳的控制问题被结合，两个算法被提出以便他们解决每个交往的机器人的动力学。潜在的功能被用来定义终端状态惩罚术语，和一个相应终端声明区域被加到优化限制。而且，包括稳定性和安全的主要问题也被讨论。模拟结果显示出建议控制策略的可行性。

Parameter Identification and Application of Slippage Kinematics for Tracked Mobile Robots

A new parameter identification method is proposed to solve the slippage problem when tracked mobile robots execute turning motions.Such motion is divided into two states in this paper:pivot turning and coupled turning between angular velocity and linear velocity.In the processing of pivot turning,the slippage parameters could be obtained by measuring the end point in a square path.In the process of coupled turning,the slippage parameters could be calculated by measuring the perimeter of a circular path and the linear distance between the start and end points.The identification results showed that slippage parameters were affected by velocity.Therefore,a fuzzy rule base was established with the basis on the identification data,and a fuzzy controller was applied to motion control and dead reckoning.This method effectively compensated for errors resulting in unequal tension between the left and right tracks,structural dimensions and slippage.The results demonstrated that the accuracy of robot positioning and control could be substantially improved on a rigid floor.

Path planning with multiple constraints and path following based on model predictive control for robotic fish

This paper discusses the path planning and path following control problems of robotic fish.In order to avoid obstacles when robotic fish swim in a complex environment,a path plan-ning method based on beetle swarm optimization(BSO)algorithm is developed.This method considers the influence of the robotic fish’s volume and motion constraints on the path planning task,which can eliminate the collision risk and meet the constraint of the minimum turning radius when the robotic fish obtains the planned path.In construct-ing the path following controller,a multilayer perception based model predictive control(MPC)is adopted to design the optimal control method,and the objective function of the optimal control is dynamically adjusted according to the path curvature.The simulation results show that this proposed method can effectively overcome the complexity of robotic fish kinematics modelling and adapt well to the reference paths of different curvatures given by the path planner.

Tracking Control of Wheeled Mobile Robots with Communication Delay and Data Loss

This paper considers the tracking control problem of a wheeled mobile robot under situation of communication delay and consecutive data packet dropouts in the feedback channel. A tracking controller in discrete-time domain for the case of ideal network condition is first derived, and then the networked predictive controller as well as two algorithms for dealing with communication delay and consecutive data packet dropouts are proposed. Simulation and experimental results verify the realizability and effectiveness of the proposed algorithms.

Longitudinal and lateral slip control of autonomous wheeled mobile robot for trajectory tracking

This research formulates a path-following control problem subjected to wheel slippage and skid and solves it using a logic-based control scheme for a wheeled mobile robot （WMR）. The novelty of the proposed scheme lies in its methodology that considers both longitudinal and lateral slip components. Based on the derived slip model, the controller for longitudinal motion slip has been synthesized. Various control parameters have been studied to investigate their effects on the performance of the controller resulting in selection of their optimum values. The designed controller for lateral slip or skid is based on the proposed side friction model and skid check condition. Considering a car-like WMR, simulation results demonstrate the effectiveness of the proposed control scheme. The robot successfully followed the desired circular trajectory in the presence of wheel slippage and skid. This research finds its potential in various applications involving WMR navigation and control.

Data-driven iterative learning trajectory tracking control for wheeled mobile robot under constraint of velocity saturation

Considering the wheeled mobile robot(WMR)tracking problem with velocity saturation,we developed a data‐driven iterative learning double loop control method with constraints.First,the authors designed an outer loop controller to provide virtual velocity for the inner loop according to the position and pose tracking error of the WMR kinematic model.Second,the authors employed dynamic linearisation to transform the dynamic model into an online data‐driven model along the iterative domain.Based on the measured input and output data of the dynamic model,the authors identified the parameters of the inner loop controller.The authors considered the velocity saturation constraints;we adjusted the output velocity of the WMR online,providing effective solutions to the problem of velocity saltation and the saturation constraint in the tracking process.Notably,the inner loop controller only uses the output data and input of the dynamic model,which not only enables the reliable control of WMR trajectory tracking,but also avoids the influence of inaccurate model identification processes on the tracking performance.The authors analysed the algorithm's convergence in theory,and the results show that the tracking errors of position,angle and velocity can converge to zero in the iterative domain.Finally,the authors used a simulation to demonstrate the effectiveness of the algorithm.

Modeling and Adaptive Control of an Omni-Mecanum-Wheeled Robot

The complete dynamics model of a four-Mecanum-wheeled robot considering mass eccentricity and friction uncertainty is derived using the Lagrange’s equation. Then based on the dynamics model, a nonlinear stable adaptive control law is derived using the backstepping method via Lyapunov stability theory. In order to compensate for the model uncertainty, a nonlinear damping term is included in the control law, and the parameter update law with σ-modification is considered for the uncertainty estimation. Computer simulations are conducted to illustrate the suggested control approach.

Robust Control Design of Wheeled Inverted Pendulum Assistant Robot

This paper examines the design concept and mobile control strategy of the human assistant robot I-PENTAR(inverted pendulum type assistant robot). The motion equation is derived considering the non-holonomic constraint of the twowheeled mobile robot. Different optimal control approaches are applied to a linearized model of I-PENTAR. These include linear quadratic regulator(LQR), linear quadratic Gaussian control(LQG), H_2 control and H_∞ control. Simulation is performed for all the approaches yielding good performance results.

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.

基于前馈非线性模型预测控制的类车机器人路径跟踪

类车机器人由于零件标准化程度低,侧偏刚度等轮胎力学参数难以准确获得,存在动力学建模十分困难的问题,因此现有研究工作通常以运动学模型作为类车机器人的控制模型,但由于其运动学模型存在模型失配,导致类车机器人与参考路径之间的误差、类车机器人的前轮转角和前轮转角速度出现剧烈振荡现象.针对前述问题,本文基于非线性模型预测控制(Nonlinear model predictive control,NMPC)的滚动优化原理,引入基于逆运动学模型的前馈转角信息,将前轮转向角作为预测模型的第四维,提出了一种基于前馈非线性模型预测控制(Feedforward NMPC,FNMPC)的类车机器人路径跟踪控制算法.并通过Simulink和CarSim进行了联合仿真,结果表明FNMPC有效减小了模型失配导致的振荡现象,同时具有较高的跟踪精度.其中前馈非线性模型预测控制器的位移误差幅值不超过0.1106 m,航向误差幅值不超过0.1253 rad.在相同工况下,线性模型预测控制、前馈线性模型预测控制、纯跟踪控制和Stanley控制误差发散,而本文提出的FNMPC相比已有NMPC跟踪精度更高,且控制增量绝对累计值相比NMPC控制器减小67.53%.通过线控类车机器人底盘作为实验平台完成的测试结果表明,NMPC系统在进入弯道时出现控制失控现象,在相同工况下,FNMPC系统能够有效完成对参考路径的跟踪,同时将位移误差幅值控制在0.1624 m以内,航向误差幅值控制在0.1138 rad以内.

Soft Robotics:Morphology and Morphology-inspired Motion Strategy

Robotics has aroused huge attention since the 1950s.Irrespective of the uniqueness that industrial applications exhibit,conventional rigid robots have displayed noticeable limitations,particularly in safe cooperation as well as with environmental adaption.Accordingly,scientists have shifted their focus on soft robotics to apply this type of robots more effectively in unstructured environments.For decades,they have been committed to exploring sub-fields of soft robotics(e.g.,cutting-edge techniques in design and fabrication,accurate modeling,as well as advanced control algorithms).Although scientists have made many different efforts,they share the common goal of enhancing applicability.The presented paper aims to brief the progress of soft robotic research for readers interested in this field,and clarify how an appropriate control algorithm can be produced for soft robots with specific morphologies.This paper,instead of enumerating existing modeling or control methods of a certain soft robot prototype,interprets for the relationship between morphology and morphology-dependent motion strategy,attempts to delve into the common issues in a particular class of soft robots,and elucidates a generic solution to enhance their performance.

海参捕捞机器人运动控制系统的仿真研究

随着水下机器人技术的发展,海参捕捞机器人将逐渐取代费时费力的人工捕捞作业。但是海参捕捞机器人的运动控制精度一直影响其运动稳定性和捕捞效率,一方面是由于海底的作业环境恶劣多变,机器人的结构功能复杂;另一方面是随着海参的累积,机器人的参数发生改变,原有控制模型的控制精度下降。为提高海参捕捞机器人的运动控制精度,在综合考虑机器人各种载荷的基础上,还考虑了海参对机器人造成的干扰,建立更加全面的机器人动力学模型;并运用模型预测控制理论和非线性干扰观测器对机器人的运动过程进行模拟分析。通过分别模拟机器人的定深下潜、运动姿态保持、路径跟踪和载重上升运动过程,定量分析机器人的运动控制精度,最后构建一个系统全面且精度较高的海参捕捞机器人运动控制系统。

物联网工控平台下移动焊接机器人焊缝轨迹跟踪控制方法

在大型物联网工控平台下,移动焊接机器人焊缝轨迹跟踪控制过程中,焊接机器人位姿参量获取困难,应用效果不理想,控制后机器人焊缝偏差仍然较大,焊缝轨迹与预期轨迹的一致性系数较低,因此,提出物联网工控平台下移动焊接机器人焊缝轨迹跟踪控制方法。在物联网工控平台内,利用角速度传感器与加速度传感器感知焊接机器人位姿参量。搭建焊接机器人运动学和动力学模型,跟踪焊接机器人焊缝轨迹,确定焊接机器人焊缝误差和调控量,利用控制器对焊缝轨迹自适应控制。经实验证明,设计方法控制下焊缝偏差在0.1 mm以内,焊缝轨迹与预期轨迹一致性系数在9以上,该方法具有良好的焊接机器人焊缝轨迹跟踪控制性能。

复杂地形六轮独立驱动与转向机器人轨迹跟踪与避障控制

为研究六轮移动机器人在复杂地形的运动控制方法,针对六轮独立驱动与转向机器人复杂地形轨迹跟踪问题,提出一种预测控制和动态补偿的控制方法。基于非完整约束的线性六轮移动机器人运动学模型,以模型预测控制算法为基础,引入比例-积分-微分补偿控制器,抑制动态滞后引起的跟踪误差,设计速度与转向角动态反馈补偿,以应对地形扰动对轨迹跟踪的影响。分析机器人运动过程中障碍物的避碰问题,设计可求解避障轨迹的避障规划器,通过轨迹跟踪系统对局部避障轨迹进行跟踪控制,实现机器人的轨迹跟踪和自动避碰。对轨迹跟踪算法和避障算法进行仿真实验。实验结果表明:在典型工况下,机器人可完成凹形斜坡、凸形斜坡和凹凸地形正弦型轨迹跟踪控制和静态与动态障碍物避碰,验证了新方法的有效性。

一种ROV型深海矿物采集装置的路径跟踪控制方法

本文针对一种新型遥控无人潜水器(Remote Operated Vehicle,ROV)拖曳采集装置(Mining Robot,MRT)的路径跟踪问题,提出一种路径跟踪控制方法。首先建立简化的ROV型深海采集装置的运动模型,随后提出一种基于线性模型预测控制算法(Linear Model Predictive Control,LMPC)和非线性模型预测控制器(Nonlinear Model Predictive Control,NMPC)的路径跟踪算法。与传统的模型预测控制器(Model Predictive Control,MPC)不同,本文提出的双层模型预测控制算法(Double Model Predictive Control,DMPC)由两部分组成:(1)由MRT的LMPC控制器计算得到MRT的速度控制律,用于快速收敛MRT的跟踪误差;(2)由ROV的NMPC控制器计算得到ROV的控制输入,用于响应MRT的速度控制律。在DMPC的设计中,有效考虑状态量和控制量约束,其中为了保证ROV控制输入的平顺性,引入ROV的控制量增量约束。最后,设计仿真实验用于验证MRT的路径跟踪效果,数值仿真结果证明了该算法的有效性。

间歇性通信下多移动机器人的分布式切换预测控制

针对间歇性通信下的多移动机器人编队,提出了一种分布式切换预测控制方法。首先,通过将切换拓扑策略描述为间歇性通信,将多机器人编队建模为一类带有路径参数同步约束项的切换系统模型,以减少通信代价。针对名义系统部分,采用分布式切换预测控制方法,给出了名义系统指数稳定的充分条件和稳定化控制器的设计方法。针对路径参数同步约束项,通过最小化具有路径参数同步约束的代价函数,给出了基于分布式预测控制路径参数同步控制器的设计方法。最后,仿真验证了所提算法能够使多移动机器人在间歇通信的条件下完成编队任务。