Robust Interaction Control of a Mobile Manipulator – Dynamic Model Based Coordination

This paper discusses the modeling and control of a spatial mobile manipulator which consists of a robotic manipulator mounted upon a wheeled mobile platform. The nonholonomic model, which assumes perfect contact between the wheels and the ground, is obtained using the Lagrange–d'Alembert formulation. Also, the dynamic model, which considers slip of the platform's tires, is developed using the Newton–Euler method and incorporates Dugoff's tire friction model. The complexity of the model is increased by introducing kinematic redundancy which is created when a multi-linked manipulator is used. The kinematic redundancy is resolved by decomposing the mobile manipulator into two subsystems; the mobile platform and the manipulator. Based on the coordination scheme used to resolve the kinematic redundancy, a robust interaction control algorithm, in which suitable controllers are designed for the two subsystems, is developed and applied. The adverse effect of the wheel slip on the tracking of commanded motion is discussed in the simulation. For the dynamic model, a robust control approach is employed to minimize the harmful effect of the wheel slip on the tracking performance. Simulation results show the promise of the developed algorithm.     

Dynamic path tracking control of a vehicle on slippery terrain

This paper deals with accuracy and reliability for the path tracking control of a four wheel mobile robot with a double-steering system when moving at high dynamics on a slippery surface. An extended kinematic model of the robot is developed considering the effects of wheel–ground skidding. This bicycle type model is augmented to form a dynamic model that considers an actuation of the four wheels. Based on the extended kinematic model, an adaptive and predictive controller for the path tracking is developed to drive the wheels front and rear steering angles. The resulting control law is combined with a stabilization algorithm of the yaw motion which modulates the actuation torque of each four wheels, on the basis of the robot dynamic model. The global control architecture is experimentally evaluated on a wet grass slippery terrain, with speeds up to 7 m/s. Experimental results demonstrate enhancement of tracking performances in terms of stability and accuracy relative to the kinematic control.     

Robust adaptive control for a nonholonomic mobile robot with unknown parameters

A robust adaptive controller for a nonholonomic mobile robot with unknown kinematic and dynamic parameters is proposed. A kinematic controller whose output is the input of the relevant dynamic controller is provided by using the concept of backstepping. An adaptive algorithm is developed in the kinematic controller to approximate the unknown kinematic parameters, and a simple single-layer neural network is used to express the highly nonlinear robot dynamics in terms of the known and unknown parameters. In order to attenuate the effects of the uncertainties and disturbances on tracking performance, a sliding mode control term is added to the dynamic controller. In the deterministic design of feedback controllers for the uncertain dynamic systems, upper bounds on the norm of the uncertainties are an important clue to guarantee the stability of the closed-loop system. However, sometimes these upper bounds may not be easily obtained because of the complexity of the structure of the uncertainties. Thereby, simple adaptation laws are proposed to approximate upper bounds on the norm of the uncertainties to address this problem. The stability of the proposed control system is shown through the Lyapunov method. Lastly, a design example for a mobile robot with two actuated wheels is provided and the feasibility of the controller is demonstrated by numerical simulations.     

Kinematic modeling,mobility analysis and design of wheeled mobile robots

Wheeled mobile robots (WMRs) consist of interconnections of many electromechanical systems. Their mechanical subsystem comprises primarily the platform and the wheel units. To formulate the kinematic model of this class of robots, we model the individual subsystems separately. The composite kinematic model of a WMR is then a coupling of the various kinematic submodels. We study WMRs with different wheels, i.e. offset wheels, centered wheels and dual-wheels. The study focuses on system mobility, which is derived using the functional matrix. We also identified the kinematic equivalence between the dual-wheel and the centered wheels, and some advantages of the dual-wheels over the centered wheels and offset wheels. Results suggest that WMRs with mobility less than 3 cannot track a trajectory with a discontinuous heading without incorporating a time delay, during which the wheel orientation should be changed. Moreover, the steering angles of WMRs equipped with steered wheels require proper coordination to avoid jamming of the drive subsystem. For design purposes, we aim at a kinetostatically robust WMR. The concept of kinetostatic isotropy is applied to find the location of the wheels with respect to the platform and their type in order to achieve isotropy. It is shown that WMRs with three conventional wheels can be made isotropic if the offset either vanishes or equals the radius of the wheel, and if the three wheels are mounted at the vertices of an equilateral triangle.     

Dynamic Modeling and Tracking Control of a Nonholonomic Wheeled Mobile Manipulator with Dual Arms

This paper presents methodologies for dynamic modeling and trajectory tracking of a nonholonomic wheeled mobile manipulator (WMM) with dual arms. The complete dynamic model of such a manipulator is easily established using the Lagrange’s equation and MATHEMATICA. The structural properties of the overall system along with its subsystems are also well investigated and then exploited in further controller synthesis. The derived model is shown valid by reducing it to agree well with the mobile platform model. In order to solve the path tracking control problem of the wheeled mobile manipulator, a novel kinematic control scheme is proposed to deal with the nonholonomic constraints. With the backstepping technique and the filtered-error method, the nonlinear tracking control laws for the mobile manipulator system are constructed based on the Lyapunov stability theory. The proposed control scheme not only achieves simultaneous trajectory and velocity tracking, but also compensates for the dynamic interactions caused by the motions of the mobile platform and the two onboard manipulators. Simulation results are performed to illustrate the efficacy of the proposed control strategy.     

基于视觉伺服反馈的不确定非完整动态移动机器人的自适应镇定

研究了带有固定在天花板上的摄像机系统的非完整动态移动机器人的镇定问题. 首先, 利用针孔摄像机模型引入了基于摄像机目标的视觉伺服运动学模型,并针对该运动学模型给出了一个运动学镇定控制器. 然后,在摄像机参数不确定的情形下设计了一个自适应滑模控制器实现了不确定动态移动机器人的镇定. 提出的控制器不仅对结构不确定性如质量变化, 而且对无结构不确定性如外部扰动都具有鲁棒性. 通过Lyapunov方法严格证明了提出的控制系统的稳定性和估计参数的有界性. 仿真结果证实了控制律的有效性.     

基于动力学模型的轮式移动机器人电机控制

针对移动机器人两路电机协同控制问题,提出基于动力学模型的轮式移动机器人电机控制律 （DMMC）．首先推导出质心位置不一定在几何中心的移动机器人运动学模型和动力学模型,并求解出两轮速 度与力矩之间的非线性微分方程．然后,基于两轮速度与力矩间非线性微分方程、电机电气方程和电机机电 方程,推导出移动机器人系统状态方程．最后采用极点配置得到I 型状态反馈控制律．仿真显示,DMMC 法实 现了对输入指令的零稳态误差快速响应．     

Dynamic control model of a cobot with three omni-wheels

In this paper, a new collaborative robot with omni-wheels has been proposed and its dynamic control has been developed and validated. Collaborative robots (Cobots) have been introduced to guide and assist human operators to move heavy objects in a given trajectory. Most of the existing cobots use steering wheels; typical drawbacks of using steering wheels include the difficulties to (i) follow a trajectory with a curvature larger than that of the base platform, (ii) mount encoders on steering wheels due to self-spinning of the wheels, and (iii) quarantine dynamic control performance since it is purely kinematic control. The new collaborative robot is proposed to overcome the above-mentioned shortcomings. The methodologies for its dynamic control are focused and the simulation has been conducted to validate the control performance of the system.     

Odometry based pose determination and errors measurement for a mobile robot with two steerable drive wheels

A trigonometric method is proposed to calculate the pose (position and orientation) of a mobile robot, possessing a locomotion platform with a unique combination of two steerable and driven wheels and two caster wheels. The model of the locomotion platform is derived to deliver timely and accurate odometer information from measurements of drive wheel revolutions and steering angles. Non-systematic errors, mainly caused by wheel slippage, are detected by a new computation method based on the ratios between the two drive wheels’ incremental distances. Real-world experiments validate the proposed model and the algorithm’s ability to detect non-systematic errors.     

Image-Based Attitude Control of a Remote Sensing Satellite

This paper deals with the image-based control of a satellite for remote sensing. Approach is demonstrated by simulation where the position of the satellite is obtained with the Simplified General Perturbations Version 3 model and its orientation by simulating its dynamic and kinematic models. For a known position and orientation of the satellite the images are obtained using the satellite’s onboard camera, simulated by the Google Earth application. The orientation of the satellite is governed by reaction wheels, which produce the required moments to the satellite. The image-based control law using SIFT image features is applied to achieve an automatic reference-point observation on the Earth’s surface. Main contributions of the paper are the following: use of the same sensor for Earth observation and attitude control, simplicity of the approach, no need for explicit calibration of camera parameters and good tracking accuracy. Demonstrated simulation results and performance analysis confirm the approach applicability.     

Robust adaptive control for mobile manipulators

This paper addresses the trajectory tracking control of a nonholonomic wheeled mobile manipulator with parameter uncertainties and disturbances. The proposed algorithm adopts a robust adaptive control strategy where parametric uncertainties are compensated by adaptive update techniques and the disturbances are suppressed. A kinematic controller is first designed to make the robot follow a desired end-effector and platform trajectories in task space coordinates simultaneously. Then, an adaptive control scheme is proposed, which ensures that the trajectories are accurately tracked even in the presence of external disturbances and uncertainties. The system stability and the convergence of tracking errors to zero are rigorously proven using Lyapunov theory. Simulations results are given to illustrate the effectiveness of the proposed robust adaptive control law in comparison with a sliding mode controller.     

Adaptive RCMAC sliding mode control for uncertain nonlinear systems

An adaptive recurrent cerebellar-model-articulation-controller (RCMAC) sliding-mode control (SMC) system is developed for the uncertain nonlinear systems. This adaptive RCMAC sliding-model control (ARCSMC) system is composed of two systems. One is an adaptive RCMAC system utilized as the main controller, in which an RCMAC is designed to identify the system models. Another is a robust controller utilized to achieve system’s robust characteristics, in which an uncertainty bound estimator is developed to estimate the uncertainty bound so that the chattering phenomenon of control effort can be eliminated. The on-line adaptive laws of the ARCSMC system are derived in the sense of Lyapunov so that the system stability can be guaranteed. Finally, a comparison between SMC and ARCSMC for a chaotic system and a car-following system are presented to illustrate the effectiveness of the proposed ARCSMC system. Simulation results demonstrate that the proposed control scheme can achieve favorable control performances for the chaotic system and car-following systems without the knowledge of system dynamic functions.     

Results on the Robust Observer-based Position Controller for Parallel Kinematic Machines

The problem of state observation and position control by output feedback for a nonlinear three degrees-of-freedom (3-DOF) parallel kinematic machine (PKM) system is considered, based on the limited signal availability (only the moving platform displacement measurements are assumed available). Unknown velocity signals are estimated via a nonlinear robust observer that is designed for the nonlinear system with observable linear dynamics part and bounded nonlinearities and disturbances, and that guarantees global exponential stability of the observation error. A proportional-derivative (PD) controller is designed to solve the position control problem, utilizing the estimated velocity, as well as the gravitation compensation, dynamic friction and external disturbance compensation for the PKM. The closed-loop system is proven to have global asymptotical stability according to the Lyapunov analysis method and LaSalle’s invariance principle. Performance of the resulting observer and controller is illustrated in a simulation study of a 3-DOF PKM. Modifications to the nonlinear observer and control law are discussed, that assure convergence of the position error and state observation error to zero when the upper bounds on the model uncertainties/disturbances are not known a priori.     

Experimental Study of Dynamic Based Feedback Linearization for Trajectory Tracking of a Four-Wheel Autonomous Ground Vehicle

In this paper, experimental study of dynamic based trajectory tracking of an autonomous ground vehicle is presented.The vehicle with two front (steering) and two rear (driving) wheels and also an on-board computer, two DC motors, two batteries and two measurement systems is a good example of an autonomous ground vehicle. The dynamic model of this vehicle is presented in the state-space form with steering and driving torques as inputs; kinematic and dynamic parameters of the model and also electrical parameters of the motors are identified, measurement systems are calibrated and the simulation of controlling this model by feedback linearization method is compared with the experiments.The results of simulations and experiments for the feedback linearization technique are compared with those of a simple PID controller and also the results for sharp turn trajectory tracking illustrate the validity of the method used and the usefulness of the built autonomous ground vehicle.     

Adaptive tracking control for uncertain dynamic nonholonomic mobile robots based on visual servoing

The trajectory tracking control problem of dynamic nonholonomic wheeled mobile robots is considered via visual servoing feedback. A kinematic controller is firstly presented for the kinematic model, and then, an adaptive sliding mode controller is designed for the uncertain dynamic model in the presence of parametric uncertainties associated with the camera system. The proposed controller is robust not only to structured uncertainties such as mass variation but also to unstructured one such as disturbances. The asymptotic convergence of tracking errors to equilibrium point is rigorously proved by the Lyapunov method. Simulation results are provided to illustrate the performance of the control law.     

Adaptive tracking control for uncertain dynamic nonholonomic mobile robots based on visual servoing

The trajectory tracking control problem of dynamic nonholonomic wheeled mobile robots is considered via visual servoing feedback.A kinematic controller is firstly presented for the kinematic model,and ...     

Fault‐tolerant path‐following control for in‐wheel‐motor‐driven autonomous ground vehicles with differential steering

Over the past several decades, the automobile industry has denoted significant research efforts to developing in‐wheel‐motor‐driven autonomous ground vehicles (IWM‐AGVs) with active front‐wheel steering. One of the most fundamental issues for IWM‐AGVs is path following, which is important for automated driving to ensure that the vehicle can track a target‐planned path during local navigation. However, the path‐following task may fail if the system experiences a stuck fault in the active front‐wheel steering. In this paper, a fault‐tolerant control (FTC) strategy is presented for the path following of IWM‐AGVs in the presence of a stuck fault in the active front‐wheel steering. For this purpose, differential steering is used to generate differential torque between the left and right wheels in IWM‐AGVs, and an adaptive triple‐step control approach is applied to realize coordinated lateral and longitudinal path‐following maneuvering. The parameter uncertainties for the cornering stiffness and external disturbances are considered to make the vehicles robust to different driving environments. The effectiveness of the proposed scheme is evaluated with a high‐fidelity and full‐car model based on the veDYNA‐Simulink joint platform.     

基于神经网络的不确定移动机器人鲁棒自适应跟踪控制

针对含运动学未知参数以及动力学模型不确定的非完整轮式移动机器人轨迹跟踪问题,基于Radical Basis Function(径向基函数)神经网络,提出了一种鲁棒自适应控制器.首先,考虑移动机器人运动学参数未知的情况,提出了一种含自适应参数的运动学控制器,用以补偿参数不确定性导致的系统误差;其次,利用神经网络控制技术,对于机器人在移动中动力学模型不确定问题,提出了一种具有鲁棒性的动力学控制器,使得移动机器人可以在不知道具体动力学模型的情况下跟踪到目标轨迹;最后利用Lyapunov稳定性理论证明了整个系统的稳定性.通过数值仿真验证了所设计的控制器的可行性.     

An Adaptive Actor-critic Algorithm with Multi-step Simulated Experiences for Controlling Nonholonomic Mobile Robots

In this paper, we propose a new algorithm of an adaptive actor-critic method with multi-step simulated experiences, as a kind of temporal difference (TD) method. In our approach, the TD-error is composed of two value- functions and m utility functions, where m denotes the number of multi-steps in which the experience should be simulated. The value-function is constructed from the critic formulated by a radial basis function neural network (RBFNN), which has a simulated experience as an input, generated from a predictive model based on a kinematic model. Thus, since our approach assumes that the model is available to simulate the m-step experiences and to design a controller, such a kinematic model is also applied to construct the actor and the resultant model based actor (MBA) is also regarded as a network, i.e., it is just viewed as a resolved velocity control network. We implement this approach to control nonholonomic mobile robot, especially in a trajectory tracking control problem for the position coordinates and azimuth. Some simulations show the effectiveness of the proposed method for controlling a mobile robot with two-independent driving wheels.     

轮子纵向打滑条件下的移动机器人自适应跟踪控制

针对纵向滑动参数未知的轮式移动机器人的轨迹跟踪问题,提出一种自适应跟踪控制策略.利用两个未知参数来描述移动机器人左右轮的纵向打滑程度,建立了产生纵向滑动的差分驱动轮式移动机器人的运动学模型;设计了补偿纵向滑动的自适应非线性反馈控制律;应用 Lyapunov 稳定性理论与 Barbalat 定理证明了闭环系统的稳定性;同时,提出了一种由极点配置方法在线调整控制器增益的方法.仿真结果验证了所提出控制方法的有效性.