Adaptive recurrent neural network control of uncertain constrained nonholonomic mobile manipulators

In this article, motion/force control problem of a class of constrained mobile manipulators with unknown dynamics is considered. The system is subject to both holonomic and nonholonomic constraints. An adaptive recurrent neural network controller is proposed to deal with the unmodelled system dynamics. The proposed control strategy guarantees that the system motion asymptotically converges to the desired manifold while the constraint force remains bounded. In addition, an adaptive method is proposed to identify the contact surface. Simulation studies are carried out to verify the validation of the proposed approach.     

Design and implementation of a block‐backstepping based tracking control for nonholonomic wheeled mobile robot

This paper presents formulation of a novel block‐backstepping based control algorithm to overcome the challenges posed by the tracking and the stabilization problem for a differential drive wheeled mobile robot (WMR). At first, a two‐dimensional output vector for the WMR has been defined in such a manner that it would decouple the two control inputs and, thereby, allow the designer to formulate the control laws for the two inputs one at a time. Actually, the decoupling has been carried out in a way to convert the system into block‐strict feedback form. Thereafter, block‐backstepping control algorithm has been utilized to derive the expressions of the control inputs for the WMR system. The proposed block‐backstepping technique has further been enriched by incorporating an integral action for enhancing the steady state performance of the overall system. Global asymptotic stability of the overall system has been analyzed using Lyapunov stability criteria. Finally, the proposed control algorithm has been implemented on a laboratory scale differential drive WMR to verify the effectiveness of the proposed control law in real‐time environment. Indeed, the proposed design approach is novel in the sense that it has judiciously exploited the nonholonomic constraint of the WMR to result in a reduced order block‐backstepping controller for the WMR, and thereby, it has eventually yielded a compact expression of the control law that is amenable to real‐time implementation. Copyright © 2015 John Wiley & Sons, Ltd.     

Switched visual servo control of nonholonomic mobile robots with field-of-view constraints based on homography

This paper presents a novel scheme for visual servoing of a nonholonomic mobile robot equipped with a monocular camera in consideration of field-of-view (FOV) constraints. In order to loosen the FOV constraints, the system states are expressed by the homography between the current frame and the key frame so that the target is not necessarily to be always visible in the control process. A switched visual controller is designed to deal with the nonholonomic constraints. Moreover, an iteration strategy is used to eliminate errors caused by the parameter uncertainty. The stablity and robustness of the proposed scheme are guaranteed by theoretical analysis. Compared to conventional schemes, the proposed approach has the following advantages: 1) a better path in Cartesian space can be achieved owing to the loosening of FOV constraints; 2) the iteration strategy ensures the robustness to parameter uncertainty; 3) when used in landmark-based navigation, it needs much sparser and simpler landmarks than those localization-based approaches need. Simulation results demonstrate the effectiveness of the proposed method.     

柔性针的运动学建模及实验研究

针对在微创手术中传统采用的钢针的不足,如与组织作用,双方均产生较大变形,造成很大误差,严重影响治疗效果。另外在手术中常常遇到一些重要的组织和器官要避开,传统的钢针无法满足需要。本文采用带斜尖的柔性针,完全利用进针时斜尖与组织的侧向作用力使针轴产生弯转。这样不但可以更精确控制针的轨迹,而且还能绕过障碍物准确达到靶点。本文首先简化了WebsterIII等人提出的柔性针非完整约束系统的自行车模型,提出了自行车前、后轮模型。在此基础上,又提出了更符合实际的带返程度的自行车模型,并进行了运动学建模研究。以实验数据拟合了模型中各参数,同时验证了此模型的合理性和准确性。     

Flocking of multi‐agent nonholonomic systems with unknown leader dynamics and relative measurements

In this paper, we consider the distributed flocking control problem of multi‐agent nonholonomic systems with a virtual leader whose dynamics is unknown; state information is time varying and not available to all agents under both fixed and switching topologies. On the basis of the relative velocity and orientation information of neighboring agents, two distributed discontinuous control protocols are designed for fixed and switching topologies, respectively. By using tools from algebraic graph theory and nonsmooth analysis, the proposed distributed discontinuous control protocols guarantee that the velocities and orientations of the agents exponentially converge to the velocity and orientation of the virtual leader, respectively, while ensuring collision avoidance of the whole group, if the interaction graph among agents is undirected and the virtual leader with bounded time‐varying velocity has directed paths to other agents. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2017 John Wiley & Sons, Ltd.     

非完整约束下的机器人运动规划算法

由非完整约束定义提出一种改进RRT(快速搜索随机树)算法,解决受动力学约束的移动机器人运动规划问题.该算法将移动机器人的非完整约束条件与RRT搜索算法相结合.针对RRT算法在全局状态空间均匀随机搜索导致算法无谓耗费代价大的缺陷,引入目标偏向思想,并选择计算复杂度低的距离参数提高求解速度.通过几类典型的非完整约束下的机器...     

链式系统轨迹跟踪控制:一种新方案

研究了链式系统的轨迹跟踪控制问题,提出了一种新的跟踪方案,设计出能实现全避轨迹跟踪的静态控制器。它克服了用动态反馈线性化方法设计出控制器的两个缺点;控制器维数高和闭环系统有奇异点,将其用于一类轮式机器人的控制中,仿真结果表明了所提出方法的有效性。     

Evolutionary Learning of a Fuzzy Behavior Based Controller for a Nonholonomic Mobile Robot in a Class of Dynamic Environments

This paper presents an approach for evolving optimum behaviors for a nonholonomic mobile robot in a class of dynamic environments. A new evolutionary algorithm reflecting some powerful features in the natural evolutionary process to have flexibility to deal with changes in the environment is used to evolve optimum behaviors. Furthermore, a fuzzy set based multi-objective fitness evaluation function is adopted in the evolutionary algorithm. The multi-objective evaluation function is designed so that it allows incorporating complex linguistic features that a human observer would desire in the behaviors of the mobile robot movements. To illustrate the effectiveness of the proposed method, simulation results are compared using a conventional evolutionary algorithm.     

Kinematic Analysis of Mobile Manipulator for Measurement and Maintenance in Dangerous Environment

This paper studies the kinematic modeling of a mobile manipulator that consists of 5-DOF manipulator and an autonomous wheeled mobile platform.Then an artificial neural network to realize the coordination motion between manipulator and mobile platform is developed.On the basis of the task specifications,the algorithm determines the appropriate control variables to respond to the well tracking trajectory.The control strategy employed for either subsystem is achieved by using a robust supervised controller.A learning paradigm is used to produce the required reference variables for an overall cooperative behavior of the sys- tem.Simulation results are presented to show the effectiveness of this approach.     

非完整自主车基于圆轨迹的道路避障

本文就四轮非完整自主车提出了一种基于圆轨迹的道路避障策略．先将道路上 的障碍按照障碍距离自主车的远近划分层次，使一个层次的障碍能在自主车视场中全部出现 ．然后给出基于圆轨迹的避障算法，即自主车沿由自主车出发位姿和子目标点确定的圆弧轨 迹走行．在此之前推导四轮非完整车的运动模型为提出避障策略的基础准备．尽量减小自主 车在走行过程中运动状态的改变，基于圆轨迹避障策略能够很好地满足这一要求．最后引入 代价函数，给出对于此方法的评价，体现了本方法的优越性．