Control Of Omnidirectional Mobile Robot Research Articles

Dynamic surface control for omnidirectional mobile robot with full state constrains and input saturation

Dynamic surface control for omnidirectional mobile robot with full state constrains and input saturation

Obstacle-avoidance trajectory planning and sliding mode-based tracking control of an omnidirectional mobile robot

Trajectory planning and tracking control play a vital role in the development of autonomous mobile robots. To fulfill the tasks of trajectory planning and tracking control of a Mecanum-wheeled omnidirectional mobile robot, this paper proposes an artificial potential field-based trajectory-planning scheme and a discrete integral terminal sliding mode-based trajectory-tracking control strategy. This paper proposes a trajectory-planning scheme and a trajectory-tracking control strategy for a Mecanum-wheeled omnidirectional mobile robot by using artificial potential field and discrete integral terminal sliding mode, respectively. First, a discrete kinematic-and-dynamic model is established for the Mecanum-wheeled omnidirectional mobile robot. Then, according to the positions of the robot, target, and obstacles, a reference an obstacle-avoidance trajectory is planned and updated iteratively by utilizing artificial potential field functions. Afterward, a discrete integral terminal sliding mode control algorithm is designed for the omnidirectional mobile robot such that the robot can track the planned trajectory accurately. Meanwhile, the stability of the control system is analyzed and guaranteed proved in the sense of Lyapunov. Last, simulations are executed in the scenarios of static obstacles and dynamic obstacles. The simulation results demonstrate the effectiveness and merits of the presented methods.

Interval type-2 fuzzy neural network-based adaptive compensation control for omni-directional mobile robot

Interval type-2 fuzzy neural network-based adaptive compensation control for omni-directional mobile robot

Fast-convergent model predictive control of omni-directional mobile robots

Fast-convergent model predictive control of omni-directional mobile robots

Predefined-Time Fuzzy Neural Network Control for Omnidirectional Mobile Robot

In this paper, a fuzzy neural network based predefined-time trajectory tracking control method is proposed for the tracking problem of omnidirectional mobile robots (FM-OMR) with uncertainties. Considering the requirement of tracking error convergence time, a position tracking controller based on predefined-time stability is proposed. Compared with the traditional position tracking control method, the minimum upper bound of the convergence time can be explicitly set. In order to obtain more accurate angular velocity tracking, the inner loop controller combines Type 1 fuzzy neural network (T1FNN) to estimate the uncertainty. In addition, considering the problem of feedback channel noise, a Kalman filter combining velocity and position information is proposed. Finally, the simulation results verify the effectiveness of this method.

Visual servoing control of omnidirectional mobile robots based on disturbance observer

This study studies a critical issue that linear velocity and steering angular velocity of the wheels of omni-directional mobile robot are easily affected by the unknown external disturbances such as wind direction and road flatness during the visual servoing stabilization task. To overcome such challenging problems, this study proposes a disturbance observer based visual servoing control strategy. In configuration, the controller is divided into two parts: the quasi-min-max model predictive controller is designed to accommodate the state constraint and input constraint of the system, and complete the visual stabilization task without disturbance. A nonlinear disturbance observer is designed to estimate the external disturbance and feedback compensate the effect of the actual disturbance on the wheel speed. The simulation results and real experiments show that the proposed control strategy can stably accomplish the visual servoing stabilization task even with a large external disturbance.

Frictional forces and torques compensation based cascaded sliding-mode tracking control for an uncertain omnidirectional mobile robot

The work presented here deals with the trajectory-tracking control of omnidirectional mobile robots using a novel robust control technique. The aim is to achieve good tracking performance in the presence of frictional forces and torques, uncertainties, and saturated control inputs. First, a dynamic model of the omnidirectional mobile robot incorporating motor dynamics and frictional forces and torques is derived leading to a higher order system model. Subsequently, a novel cascaded sliding-mode tracking control scheme is proposed to perform trajectory-tracking with the omnidirectional mobile robot, which includes direct and indirect sliding-mode controllers in a cascaded structure. The indirect sliding-mode controller is utilized to attain tracking of the indirect reference input (i.e., desired trajectory) in the first subsystem and constitutes a direct reference input for the second one. A direct sliding-mode controller (i.e., actual control) is then designed to achieve tracking of the direct reference input. This way, the indirect reference input can be effectively manipulated through the proposed cascaded sliding-mode tracking control and individual subsystems are guaranteed to have not only Uniform Ultimate Boundedness but also asymptotic convergent performance. The stability of the closed-loop system is demonstrated via the Lyapunov stability criteria and validated through simulations. It is shown that the cascaded sliding-mode tracking control leads to good trajectory-tracking performance in the presence of uncertainties, friction, and saturated control input.

Mechanism and Control of Omnidirectional Mobile Robot with Multiple Steering and Drive Wheels

Mechanism and Control of Omnidirectional Mobile Robot with Multiple Steering and Drive Wheels

Fast-convergent model predictive control of omni-directional mobile robots

Fast-convergent model predictive control of omni-directional mobile robots

Adaptive Fuzzy Sliding Mode Control of Omnidirectional Mobile Robots with Prescribed Performance

Adaptive fuzzy sliding-mode control design for omnidirectional mobile robots with prescribed performance is presented in this work. First, an error transformation which transforms the constrained variable into an unconstrained one is carried out. Next, a fuzzy logic system (FLS) for approximating the unknown dynamics is constructed. Based on such a model, a nominal adaptive linearizing controller incorporating a serial-parallel model (SPM)-based composite algorithm, which improves the tracking performance of the overall closed-loop system, is synthesized. To solve the so-called “loss of controllability” problem, a smooth-switching algorithm is embedded which hands over the control authority to an auxiliary sliding-mode controller until the danger is safely bypassed. The proposed design ensures the semi-globally uniformly ultimately bounded stability of the closed-loop signals. Simulation works demonstrating the validity of the proposed design are presented in the final.

Modeling and Nonlinear Adaptive Control for Omnidirectional Mobile Robot

This study presents a complete model for RobotinoMD an omnidirectional mobile robot. This model includes the kinematics and dynamics. It is used for the simulation and design of an adaptive nonlinear control system. The hierarchical control system that is proposed has three levels. The level-one which is the inner loop is used to control the DC motors that drive the robot wheels. A control design method combining an adaptive feedback linearization technique and the Backstepping approach is used to find the controller equation. The adaptation module that is included in the control system maintains the performance of the system in the presence of uncertainties on the inertia, weight and other parameters in the robot dynamics. The level-one controller receives its reference signal from the level-two controller which converts the linear and rotational speeds into desired speeds. This level-two controller receives its reference signal from the level-three controller which is the outer loop controller. The level-three controller equation is found so that the robot can follow a desired path described in a Cartesian space. The proposed control system is evaluated in simulation in the MATLAB-SIMULINK environment. It is compared to a PID controller. Simulation results show that the nonlinear adaptive controller has better performances.

Hierarchical fuzzy obstacle avoidance control of omnidirectional mobile robot for substation inspection

There are some limitations in the practical application of robot obstacle avoidance control methods. In order to realize the high-speed planning and obstacle avoidance processing of mobile robot, the path model, inspection route and path obstacles of the robot must be fully considered. Through feature extraction, the reasonable planning of substation inspection obstacle avoidance route is realized, and the control quantity set satisfying substation inspection is given. The hierarchical fuzzy obstacle avoidance control method of mobile robot is realized by using the optimal control set design. The simulation results show that the control method can solve various complex problems when the robot contour collides with obstacles, and can realize safe and fast control. The flexibility and robustness of obstacle avoidance are improved, and the motion state and speed of obstacles are also improved.

Adaptive Robust Constraint Following Control for Omnidirectional Mobile Robot: An Indirect Approach

The tracking performance of mobile robot is often affected by uncertainties from the deviation of initial conditions, external disturbances and varying loads, etc. An Udwadia-Kalaba based adaptive robust control is proposed for the trajectory tracking of an omnidirectional mobile robot in the presence of uncertainties. The proposed control includes nominal control part based on Udwadia-Kalaba theory and adaptive robust control part. The desired trajectory is considered as a virtual servo constraint applied to the robot system and converted into the second order standard form. So that the analytical form of constraint force could be obtained via Udwadia-Kalaba Fundamental Equation (UKFE). The system will precisely obey the given constraint (i.e., the desired trajectory) under the obtained constraint force in ideal cases. No auxiliary variables are required and it is effective whether the constraints are holonomic or nonholonomic. The designed adaptive law is in leakage type and the adaptive parameters are adjusted according to the performance of the system in order to compensate for the effect caused by uncertainty in the system. No extra information of uncertainty is needed except for the existence of uncertainty bound. Comparing with PID control, it can be found that the proposed control has better performance and can realize higher precision trajectory tracking control.

Fuzzy-Based Fault-Tolerant Control for Omnidirectional Mobile Robot

The motion-planning problem is well known in robotics; it aims to find a free-obstacle path from a starting point to a destination. To make use of actuation generosity and the fuzzy fast response behavior compared to other non-linear controllers, a fuzzy-based fault-tolerant control for an omnidirectional mobile robot with four Mecanum wheels is proposed. The objective is to provide the robot with an online scheme to control the robot motion while moving toward the final destination with avoiding obstacles in its environment and providing an adaptive solution for a combination of one or combination of the wheel’s faults. The faults happen when the wheel does not receive the control command signal from the controller; in this case, the robot can rotate freely due to the interaction with the ground. The principle of fuzzy-based control proposed by Sugeno is used to develop the motion controller. The motion controller consists of two main controllers: the Run-To-Goal, and the obstacle-avoidance controller. The outputs of these two controllers are superposed to get the net potential force on the robot. By its simplicity, the fuzzy controller can be suitable for online applications (online path planning in our case). To the best of our knowledge, this is the first fuzzy-based fault-tolerant controller for an omnidirectional robot. The proposed controller is tested by a set of simulation scenarios to check the proposed fuzzy tolerant control. Kuka OmniRob is used as an example of the omnidirectional robot in these simulation runs. Matlab is used to build the fuzzy-based fault-tolerant control, and the 3D simulation is developed on the CoppeliaSim software. We examine five distinct scenarios, each one with a different fault state. In all scenarios, the proposed algorithm could control the robot to reach its final destination with the absence and presence of an obstacle in the workspace, despite actuator faults, without crossing the workspace boundaries.

Network-Oriented Real-Time Embedded System Considering Synchronous Joint Space Motion for an Omnidirectional Mobile Robot

This paper proposes a real-time embedded system for joint space control of omnidirectional mobile robots. Actuators driving an omnidirectional mobile robot are connected in a line topology which requires synchronization to move simultaneously in translation and rotation. We employ EtherCAT, a real-time Ethernet network, to control servo controllers for the mobile robot. The first part of this study focuses on the design of a low-cost embedded system utilizing an open-source EtherCAT master. Although satisfying real-time constraints is critical, a desired trajectory on the center of the mobile robot should be decomposed into the joint space to drive the servo controllers. For the center of the robot, a convolution-based path planner and a corresponding joint space control algorithm are presented considering its physical limits. To avoid obstacles that introduce geometric constraints on the curved path, a trajectory generation algorithm considering high curvature turning points is adapted for an omnidirectional mobile robot. Tracking a high curvature path increases mathematical complexity, which requires precise synchronization between the actuators of the mobile robot. An improvement of the distributed clock—the synchronization mechanism of EtherCAT for slaves—is presented and applied to the joint controllers of the mobile robot. The local time of the EtherCAT master is dynamically adjusted according to the drift of the reference slave, which minimizes the synchronization error between each joint. Experiments are conducted on our own developed four-wheeled omnidirectional mobile robot. The experiment results confirm that the proposed system is very effective in real-time control applications for precise motion control of the robot even for tracking high curvature paths.

Trajectory tracking control based on disturbance observer for omnidirectional mobile robot

This brief focuses on the problem of trajectory tracking control of omnidirectional mobile robot with unknown external disturbances. It is assumed that the derivative of the external disturbances is bounded. The control scheme is divided into two parts. In the first part, the external disturbances are estimated by the disturbance observer. Furthermore, the feasibility of the disturbance observer is demonstrated. In the second part, we propose the trajectory tracking controller. Based up on Lyapunov function, the stability of the closed-loop system is analysed. Finally, simulations are given to show the validity of the results.

Embedded System for Motion Control of an Omnidirectional Mobile Robot

In this paper, an embedded system for motion control of omnidirectional mobile robots is presented. An omnidirectional mobile robot is a type of holonomic robots. It can move simultaneously and independently in translation and rotation. The RoboCup small-size league, a robotic soccer competition, is chosen as the research platform in this paper. The first part of this research is to design and implement an embedded system that can communicate with a remote server using a wireless link, and execute received commands. Second, a fuzzy-tuned proportional–integral (PI) path planner and a related low-level controller are proposed to attain optimal input for driving a linear discrete dynamic model of the omnidirectional mobile robot. To fit the planning requirements and avoid slippage, velocity, and acceleration filters are also employed. In particular, low-level optimal controllers, such as a linear quadratic regulator (LQR) for multiple-input-multiple-output acceleration and deceleration of velocity are investigated, where an LQR controller is running on the robot with feedback from motor encoders or sensors. Simultaneously, a fuzzy adaptive PI is used as a high-level controller for position monitoring, where an appropriate vision system is used as a source of position feedback. A key contribution presented in this research is an improvement in the combined fuzzy-PI LQR controller over a traditional PI controller. Moreover, the efficiency of the proposed approach and PI controller are also discussed. Simulation and experimental evaluations are conducted with and without external disturbance. An optimal result to decrease the variances between the target trajectory and the actual output is delivered by the onboard regulator controller in this paper. The modeling and experimental results confirm the claim that utilizing the new approach in trajectory-planning controllers results in more precise motion of four-wheeled omnidirectional mobile robots.

Predictive Control of Mobile Robot Using Kinematic and Dynamic Models

This paper presents a predictive control of omnidirectional mobile robot with three independent driving wheels based on kinematic and dynamic models. Two predictive controllers are developed. The first is based on the kinematic model and the second is founded on the dynamic model. The optimal control sequence is obtained by minimizing a quadratic performance criterion. A comparison has been done between the two controllers and simulations have been done to show the effectiveness of the predictive control with the kinematic and the dynamic models.

Model-based PI–fuzzy control of four-wheeled omni-directional mobile robots

The purpose of this study is to suggest and examine a PI–fuzzy path planner and associated low-level control system for a linear discrete dynamic model of omni-directional mobile robots to obtain optimal inputs for drivers. Velocity and acceleration filtering is also implemented in the path planner to satisfy planning prerequisites and prevent slippage. Regulated drivers’ rotational velocities and torques greatly affect the ability of these robots to perform trajectory planner tasks. These regulated values are examined in this research by setting up an optimal controller. Introducing optimal controllers such as linear quadratic tracking for multi-input–multi-output control systems in acceleration and deceleration is one of the essential subjects for motion control of omni-directional mobile robots. The main topics presented and discussed in this article are improvements in the presented discrete-time linear quadratic tracking approach such as the low-level controller and combined PI–fuzzy path planner with appropriate speed monitoring algorithm such as the high-level one in conditions both with and without external disturbance. The low-level tracking controller presented in this article provides an optimal solution to minimize the differences between the reference trajectory and the system output. The efficiency of this approach is also compared with that of previous PID controllers which employ kinematic modeling. Utilizing the new approach in trajectory-planning controller design results in more precise and appropriate outputs for the motion of four-wheeled omni-directional mobile robots, and the modeling and experimental results confirm this issue.

퍼지 다층 제어기를 이용한 전방향 이동로봇의 추적제어에 관한 연구

사람이 생활하는 환경에서 일반적인 휠베이스 이동(Mobility) 방식의 로봇은 장애물에 둘러싸여 로봇의 움직임에 있어 자유로운 주행 제약을 받게 된다. 장애물을 신속하게 회피하려면 회전과정 없이 단순히 좌우 이동만 하면 되는 홀로노믹(Holonomic) 시스템 특성의 이동로봇이 필요하다. 본 논문에서는 세 개의 옴니휠(Omni-Wheels)을 사용한 홀로노믹 이동로봇의 추적제어기를 개발한다. 옴니휠을 이용한 이동로봇은 시스템 파라미터의 불확실성(uncertainty)으로 인하여 선형 제어기로는 추적제어가 매우 어려운 상황이다. 그러므로 강인성이 탁월한 퍼지 제어기를 이용한 퍼지 적응 제어 기법을 설계하여 옴니휠 이동 로봇의 추적제어(tracking control) 성능을 높인다. 본 논문에서 제어 대상 시스템의 매개 변수의 불확실성에 강인한 퍼지 제어기를 병렬로 설계하고 시스템 인식(system identification)을 이용하여 대상 시스템이 특성 변화에 적절히 대처할 수 있는 적합한 퍼지 제어기를 선택한 후 피드백 제어를 실행하는 퍼지 다층 제어기(Fuzzy Multi-Layered Controller) 시스템을 이용한 적응 제어기법을 제시한다. 고전 적응 제어기와 기존 퍼지 적응 제어기의 문제점을 극복한 퍼지 적응 제어기를 도입하여 강인 제어기를 병렬로 설계하고 시스템 인식을 이용하여 대상 시스템의 특성 변화에 적절히 대처할 수 있는 적합한 퍼지 제어기를 선택한 후 피드백 제어를 실행하는 퍼지 다층 제어기(FMLC)를 제시한다. The trajectory control for omni-directional mobile robot is not easy. Especially, the tracking control which system uncertainty problem is included is much more difficult. This paper develops trajectory controller of 3-wheels omni-directional mobile robot using fuzzy multi-layered algorithm. The fuzzy control method is able to solve the problems of classical adaptive controller and conventional fuzzy adaptive controllers. It explains the architecture of a fuzzy adaptive controller using the robust property of a fuzzy controller. The basic idea of new adaptive control scheme is that an adaptive controller can be constructed with parallel combination of robust controllers. This new adaptive controller uses a fuzzy multi-layered architecture which has several independent fuzzy controllers in parallel, each with different robust stability area. Out of several independent fuzzy controllers, the most suited one is selected by a system identifier which observes variations in the controlled system parameter. This paper proposes a design procedure which can be carried out mathematically and systematically from the model of a controlled system; related mathematical theorems and their proofs are also given. Finally, the good performance of the developed mobile robot is confirmed through live tests of path control task.