Designing approach on trajectory-tracking control of mobile robot

Based on differential geometry theory, applying the dynamic extension approach of relative degree, the exact feedback linearization on the kinematic error model of mobile robot is realized. The trajectory-tracking controllers are designed by pole-assignment approach. When angle speed of mobile robot is permanently nonzero, the local asymptotically stable controller is designed. When angle speed of mobile robot is not permanently nonzero, the trajectory-tracking control strategy with globally tracking bound is given. The algorithm is simple and applied easily. Simulation results show their effectiveness.     

A new multisensor fusion SLAM approach for mobile robots

This paper presents a novel method, which enhances the use of external mechanisms by considering a multisensor system, composed of sonars and a CCD camera. Monocular vision provides redundant information about the location of the geometric entities detected by the sonar sensors. To reduce ambiguity significantly, an improved and more detailed sonar model is utilized. Moreover, Hough transform is used to extract features from raw sonar data and vision image. Information is fused at the level of features. This technique significantly improves the reliability and precision of the environment observations used for the simultaneous localization and map building problem for mobile robots. Experimental results validate the favorable performance of this approach.     

A new space and time sensor fusion method for mobile robot navigation

To fully utilize the information from the sensors of mobile robot, this paper proposes a new sensor‐fusion technique where the sample data set obtained at a previous instant is properly transformed and fused with the current data sets to produce a reliable estimate for navigation control. Exploration of an unknown environment is an important task for the new generation of mobile service robots. The mobile robots may navigate by means of a number of monitoring systems such as the sonar‐sensing system or the visual‐sensing system. Notice that in the conventional fusion schemes, the measurement is dependent on the current data sets only. Therefore, more sensors are required to measure a given physical parameter or to improve the reliability of the measurement. However, in this approach, instead of adding more sensors to the system, the temporal sequences of the data sets are stored and utilized for the purpose. The basic principle is illustrated by examples and the effectiveness is proved through simulations and experiments. The newly proposed STSF (space and time sensor fusion) scheme is applied to the navigation of a mobile robot in an environment using landmarks, and the experimental results demonstrate the effective performance of the system. © 2004 Wiley Periodicals, Inc.     

Finite-time control of mobile robot systems with unmeasurable angular and linear velocities via bioinspired neurodynamics approach

This paper addresses the stability analysis and adaptive robust finite-time bioinspired neurodynamics control for a class of mobile robot systems with unmeasurable angular and linear velocities, and time-varying bounded disturbance. The error system of the mobile robot is decomposed into two subsystems based on the system model. The state feedback control laws with observers are designed for the two subsystems, and the adaptive robust finite-time bioinspired neurodynamics controller (ARFBNC) is designed based on the state feedback control laws and two subsystems. The stability conditions in the form of linear matrix inequalities (LMIs) are derived by introducing the Lyapunov–Krasovskii functional. The unmeasurable angular and linear velocities, and time-varying bounded disturbance are estimated effectively by employing the state feedback control laws with observers. The smooth bounded outputs are obtained and the sharp jumps of initial values for the state variables are reduced. The closed-loop system is asymptotically stable and the state errors converge to an adjustable bounded region by introducing the Lyapunov–Krasovskii functional. The simulations are performed to show the effectiveness of the proposed methods.     

基于T-S模型的轮式移动机器人轨迹跟踪控制

针对带有执行机构饱和约束与外部干扰的轮式移动机器人,提出了一种基于T-S模糊模型的轨迹跟踪方法.利用机器人运动特性和参考轨迹建立轨迹跟踪的误差系统并将其作T-S模型描述.通过求解具有LMI约束的半定规划问题,对每个线性子系统单独设计满足控制约束与H∞性能约束的状态反馈控制器,并在PDC(动态平行分配补偿)设计框架下构建全局控制器,最后证明闭环系统的李雅普诺夫稳定性.仿真结果验证了该方法的有效性和可行性.     

Global exponential tracking control of a mobile robot system via aPE condition

This paper presents the design of a differentiable, kinematic control law that achieves global asymptotic tracking. In addition, we also illustrate how the proposed kinematic controller provides global exponential tracking provided the reference trajectory satisfies a mild persistency of excitation (PE) condition. We also illustrate how the proposed kinematic controller can be slightly modified to provide for global asymptotic regulation of both the position and orientation of the mobile robot. Finally, we embed the differentiable kinematic controller inside of an adaptive controller that fosters global asymptotic tracking despite parametric uncertainty associated with the dynamic model. Experimental results are also provided to illustrate the performance of the proposed adaptive tracking controller.     

Adaptive tracking control of a wheeled mobile robot via anuncalibrated camera system

This paper considers the problem of position/orientation tracking control of wheeled mobile robots via visual servoing in the presence of parametric uncertainty associated with the mechanical dynamics and the camera system. Specifically, we design an adaptive controller that compensates for uncertain camera and mechanical parameters and ensures global asymptotic position/orientation tracking. Simulation and experimental results are included to illustrate the performance of the control law.     

Visual approach skill for a mobile robot using learning and fusion of simple skills

This paper presents a reinforcement learning algorithm which allows a robot, with a single camera mounted on a pan tilt platform, to learn simple skills such as watch and orientation and to obtain the complex skill called approach combining the previously learned ones. The reinforcement signal the robot receives is a real continuous value so it is not necessary to estimate an expected reward. Skills are implemented with a generic structure which permits complex skill creation from sequencing, output addition and data flow of available simple skills.     

A new adaptive tracking control scheme of wheeled mobile robot without longitudinal velocity measurement

This paper proposes a new adaptive trajectory tracking control scheme of the wheeled mobile robot without longitudinal velocity measurement. First, based on a kinematic controller, we obtain a new tracking error equation, which is suitable to develop an adaptive controller. Then, we develop a new adaptive trajectory tracking controller, which does not need any accurate values of the wheeled mobile robot parameters, including the driving motor parameters. Moreover, as the longitudinal velocity measurement is still difficult, this controller is developed without longitudinal velocity measurement. In addition, this new adaptive controller introduces a method to improve the control performance. The stability of the closed‐loop system is presented using the direct Lyapunov method. Finally, numerous simulations verify the effectiveness of the new controller.     

一种移动机器人路径规划新算法

快速搜索随机树（Rapidly-exploring random Tree Star,RRT*）算法在移动机器人实际应用中规划路径在转向部分存在较多的冗余转折点,导致移动机器人在移动转向过程中出现多次停顿与转向,为剔除规划路径中的冗余路径点,提高机器人移动流畅性,提出一种改进的 RRT*算法。算法将局部逆序试连法引入移动机器人路径规划,在确保RRT*算法概率完备性和渐进最优性的前提下,剔除规划路径中的冗余路径节点,使最终路径更加接近最短路径。通过MATLAB仿真实验证明,规划路径平均长度缩短4%,算法耗时缩短35%,改进后的RRT*算法能缩短规划路径且转向部分路径更加平滑。最后,使用改进后的RRT*算法在室内环境下进行移动机器人路径规划实验。实验结果表明：规划路径上无冗余路径点,且移动机器人沿路径移动流畅。     

Fuzzy control of a mobile robot

This paper describes the design of a new fuzzy logic-based navigation algorithm for autonomous robots. This design effectively achieves correct environment modeling and noisy and uncertain sensory data processing on low-cost hardware equipment. A hierarchical control strategy is presented in which three different reactive behaviors are fused in a single control law by means of a fuzzy supervisor guaranteeing robot safety and task accomplishment. Due to the inherent transparency of fuzzy logic, the proposed algorithm is computationally light, easily reconfigurable, and well-performing in a wide range of differing operating conditions and environments     

A distributed control architecture for an autonomous mobile robot

This paper describes a Distributed Control Architecture for an autonomous mobile robot. We start by characterizing the Conceptual Levels into which the various problem-solving activities of a mobile robot can be classified. In sequence, we discuss a Distributed Control System that provides scheduling and coordination of multiple concurrent activities on a mobile robot. Multiple Expert Modules are responsible for the various tasks and communicate through messages and over a Blackboard. As a testbed, the architecture of a specific system for Sonar-Based Mapping and Navigation is presented, and a distributed implementation is described.     

Autonomous mobile robot model predictive control

This paper presents model predictive control of an autonomous vehicle. Simulation and experimental results have been shown and compared with input–output linearization method. The results obtained show that the MPC is an efficient method that allows for accurate control and navigation of an autonomous vehicle. Model based predictive control is tested in simulations for motion on an inclined plane. This is done to prepare future work regarding the avoidance of the violation of the smoothness condition for exact linearization, while at the same time by modifying the input commands the geometric path planning results are conserved. The approach is presented for the wheel-ground slippage and tip-over avoidance of the three-wheeled vehicle for inclined plane motion. A complete three-dimensional dynamic model using Newtonian dynamics is also presented. Simulation results using a three-wheeled vehicle built in our laboratory illustrate the performance of the proposed controller.     

A continuous dynamic modeling approach for an omnidirectional mobile robot

MY wheel-II is one of switch omnidirectional wheel mechanisms. The omnidirectional mobile robot based on MY wheels-II is a switched non-linear system (i.e. discontinuous system). The aim of this paper is to propose a continuous modeling approach which can be employed to derive a continuous model from any given discontinuous robot dynamic model. This approach results in a continuous non-linear parameter varying (NLPV) model, and offers one solution for model-based control design. Firstly, our previously proposed average dynamic modeling approach is analyzed. We find that this modeling approach is effective only for a specific class of robot configurations. To overcome this problem, we first derive the switching conditions of MY wheel-II. Based on derived switching conditions, we then propose a simple continuous NLPV modeling approach. The new approach replaces the real discontinuous contact radius in the discontinuous dynamic model with an adaptive continuous curve. An illustrative example of the adaptive continuous curve design is provided. Both simulation and experimental results verify the effectiveness of the proposed NLPV modeling approach against the average modeling approach.     

A new approach to robust position/force control of flexible-joint robot manipulators

In this paper a new approach employing smooth robust compensators is proposed for the control of uncertain elastic-joint robot manipulators during contact tasks. It is assumed that the flexible-joint manipulators consist of two subsystems: the rigid subsystem and the flexible subsystem. The output of the flexible subsystem is assumed to be the input of the rigid subsystem. The control design is carried out in two steps. First, a desired input is designed for the rigid subsystem, which can robustly stabilize it. Second, a robust controller is designed to stabilize the flexible subsystem so that it generates the necessary torque designed for the rigid subsystem. By using this approach, the robot manipulator can exert a preset amount of force on the environment while tracking a desired trajectory with global asymptotic stability. Lyapunov's direct method is used here to prove the global asymptotic stability of the closed-loop system. The assumption of weak joint elasticity is relaxed and exact knowledge of joint stiffness is not required for the control design. Also, exact knowledge of robot kinematic and dynamic parameters and actuator parameters are not required. Unlike other approaches, this approach takes the environmental stick-slip friction as well as its dependency on normal contact force into consideration. It compensates for the adverse effects of the stick-slip friction. The proposed controller produces a smooth control action, and ensures smooth motion on the contact surface. The efficacy of the proposed controller is illustrated with the help of a numerical example of a two-link flexible-joint robot. © 1996 John Wiley & Sons, Inc.     

多传感器信息融合伺服的移动机器人快速跟随

针对移动机器人快速跟随任务的需要,采取了多传感器信息融合的伺服控制,用双目摄像机对移动机器人进行视觉导航,利用激光雷达和超声波传感器完成移动机器人的避障设计,通过位于机器人轮部的光电编码器反馈信息处理实现机器人的自定位,语音交互和手势交互共同完成移动机器人的人机交互,制定了移动机器人快速跟随整体策略并提出了软硬件系统集成方案.在实验环境中通过实验和实践表明了移动机器人能够快速顺利的完成跟随任务.     

Navigation control for a mobile robot

This article describes a navigation method of a mobile robot which uses a single camera and a guide mark. A travel path is instructed to the robot by means of path drawn on a monitor screen. The image of the guide mark provides information regarding the robot's position and heading direction. The heading direction is adjusted while moving if any deviation from the specified path is detected. The proposed method has been implemented in a mobile robot which runs at the average speed of 2.5 ft/s. without deviating more than one foot from the specified path in an indoor environment. © 1994 John Wiley & Sons, Inc.     

A new hybrid algorithm for path planning of mobile robot

The Journal of Supercomputing - The selection of algorithm is the most critical part in the mobile robot path planning. At present, the commonly used algorithms for path planning are genetic...     

An approach to learning mobile robot navigation

This paper describes an approach to learning an indoor robot navigation task through trial-and-error. A mobile robot, equipped with visual, ultrasonic and laser sensors, learns to servo to a designated target object. In less than ten minutes of operation time, the robot is able to navigate to a marked target object in an office environment. The central learning mechanism is the explanation-based neural network learning algorithm (EBNN). EBNN initially learns function purely inductively using neural network representations. With increasing experience, EBNN employs domain knowledge to explain and to analyze training data in order to generalize in a more knowledgeable way. Here EBNN is applied in the context of reinforcement learning, which allows the robot to learn control using dynamic programming.     

三轮驱动移动机器人轨迹跟踪控制

针对三轮驱动移动机器人在轨迹跟踪控制过程中运动不平滑的问题,建立了移动机器人在一定运动约束条件下的运动学模型。根据移动机器人位姿误差微分方程的描述,设计了基于后退时变状态反馈方法的移动机器人轨迹跟踪控制器。基于李雅普诺夫方法,对轨迹跟踪控制器的稳定性进行了分析,证明了该控制器能够保证闭环系统全局一致渐进稳定。仿真结果验证了运动学模型的正确性,以及轨迹跟踪控制器的有效性。