Dynamic Model Of Mobile Robot Research Articles

Trajectory Tracking of Mobile Robot Based on Improved Hierarchical Sliding Mode Control

A control algorithm based on PD control and non-singular terminal hierarchical sliding mode control is proposed for tracking control of mobile robot systems. First establish a dynamic model of mobile robot under cartesian coordinate system, the system can be divided into subsystems of posture and position, attitude subsystem by using PD control, location subsystem using non-singular terminal hierarchical sliding mode control, the introduction of the system state higher order term, improve the system in the convergence speed and stability of the sliding surface, the system reaches a steady state in a limited time; Finally, the stability of the system is proved theoretically, and the effectiveness of the control method is verified by simulation.

Omnidirectional Mobile Robot Dynamic Model Identification by NARX Neural Network and Stability Analysis Using the APLF Method

In this paper, the NARX neural network system is used to identify the complex dynamics model of omnidirectional mobile robot while rotating with moving, and analyze its stability. When the mobile robot model rotates and moves at the same time, the dynamic model of the mobile robot is complex and there is motion coupling. The change of the model in different states is a kind of symmetry. In order to solve the problem that there is a big difference between the mechanism modeling motion simulation and the actual data, the dynamic model identification of mobile robot in special state based on NARX neural network is proposed, and the stability analysis method is given. To verify that the dynamic model of NARX identification is consistent with that of the mobile robot, the Activation Path-Dependent Lyapunov Function (APLF) algorithm is used to distinguish the NARX neural network model expressed by LDI. However, the APLF method needs to calculate a large number of LMIs in practice and takes a lot of time, and, to solve this problem, an optimized APLF method is proposed. The experimental results verify the effectiveness of the theoretical method.

Robust mobile robot navigation using fuzzy type 2 with wheel slip dynamic modeling and parameters uncertainties

ABSTRACT In this paper, a full dynamic model for mobile robot with wheel slip is developed for robust navigation. The type 2 fuzzy logic controller algorithm is implemented and compared to the type 1 fuzzy controller using a differential drive wheels mobile robot (DDWMR) in the presence of wheel slipping from the perspective of control design. We present a dynamic model that explicitly relates perturbations to the vehicle slipping and parameters uncertainties. Both controllers are validated on different behaviors of navigation to evaluate their performances. Furthermore, many advanced robustness tests (modeling errors, localization uncertainties, loss of efficiency of motors, sliding ground) are established to compare the efficiency of each controller. Type 1 and interval type 2 fuzzy logic controllers are validated using V-REP robotic simulator on MATLAB® environment and real scenario are considered. The obtained results show clearly the performances of the IT2FLC comparing to the T1FLC controller especially when significant wheel slip and parameters uncertainty are considered.

Fuzzy Logic Controller for Obstacle Avoidance of Mobile Robot

Abstract This work describes design and implementation of a navigation and obstacle avoidance controller using fuzzy logic for four-wheel mobile robot. The main contribution of this paper can be summarized in the fact that single fuzzy logic controller can be used for navigation as well as obstacle avoidance (static, dynamic and both) for dynamic model of four-wheel mobile robot. The bond graph is used to develop the dynamic model of mobile robot and then it is converted into SIMULINK block by using ‘S-function’ directly from SYMBOLS Shakti bond graph software library. The four-wheel mobile robot used in this work is equipped with DC motors, three ultrasonic sensors to measure the distance from the obstacles and optical encoders to provide the current position and speed. The three input membership functions (distance from target, angle and distance from obstacles) and two output membership functions (left wheel voltage and right wheel voltage) are considered in fuzzy logic controller. One hundred and sixty-two sets of rules are considered for motion control of the mobile robot. The different case studies are considered and are simulated using MATLAB-SIMULINK software platform to evaluate the performance of the controller. Simulation results show the performances of the navigation and obstacle avoidance fuzzy controller in terms of minimum travelled path for various cases.

Mobile robot positioning method based on multi-sensor information fusion laser SLAM

A mobile robot positioning method based on multi-sensor information fusion under wireless sensor network (WSNs), called HCKF algorithm, is proposed in this Article to improve the accuracy of mobile robot positioning method. Firstly, the degree of information fusion among sensors was measured according to differences in membership degree of certain Features in different sensor information under different positioning modes, and the weight of different sensors during fusion was determined with membership degree, so as to define the membership degree of same Features among different sensors after information fusion; secondly, a testing environment for mobile robot positioning based on WSN network was established in a gymnasium and was combined with dynamic model of mobile robot for comparison of positioning accuracy of the algorithm proposed. The results show that, under two circumstances of: with noise jamming and with unknown noise jamming, positioning accuracy of the algorithm proposed in this Article is improved by 7 and 15% respectively as compared with the contrast algorithm. The effectiveness of the method proposed in this Article in mobile robot positioning is verified by the results above.

A model-based fault diagnosis scheme for wheeled mobile robots

In this paper, a fault diagnosis scheme for wheeled mobile robots is presented. In the fault detection module, a nonlinear observer is designed based on the mobile robot dynamic model. A fault is detected when at least one of the residuals exceeds its corresponding threshold. After the fault is detected, the fault isolation module is activated to isolate three types of fault: right wheel fault, left wheel fault, and other changing dynamic parameter faults. Three simulation examples are performed to show the effect of each fault to the tracking performance of mobile robot in a real situation. The simulation results demonstrate the effectiveness of our proposed approach for fault detection and isolation in wheeled mobile robots.

MMaMS 2014 Dynamic Model of a Mobile Robot

The contribution presents the dynamic model of a differential two-wheeled mobile robot in the joint frame, i.e. in the plane of angular position of both the right-hand side wheel and the left-hand side one. The aim is to create an appropriate MIMO plant model for the purpose of the mobile robot motion control synthesis. Based on the Lagrangian formalism, the complete description of the second order matrix differential equation (the dynamic model of the mobile robot) is provided, including the influence of inertial coupling forces. A pair of wheel driving torques represents the input of given model. Additionally, a decoupled dynamic model for the robust motion control implementation is presented.

이동물체 추적을 위한 이동로봇의 대형제어

The mobile robot controller is designed to track the target and to maintain the formation at the same time. Formation control is included in mobile robot controller by extending the trajectory tracking algorithm. The dynamic model of mobile robot is used with kinematic model considering the practical physical parameters of mobile robot. The dynamic model of mobile robot transforms velocity control input of kinematic model into torque control input which is the practical control input of mobile robot. Formation controller of mobile robot is designed to satisfy Lyapunov stability by backstepping method. The designed formation controller is applied to the mobile robot for various target movements and simulated to confirm the Lyapunov stability.

Formation control and trajectory tracking of mobile robotic systems – a Linear Algebra approach

SUMMARYA novel approach for trajectory tracking of a mobile-robots formation by using linear algebra theory and numerical methods is presented in this paper. The formation controller design is based on the formation states concept and the dynamic model of a unicycle-like nonholonomic mobile robot. The proposed control law designed is decentralized and scalable. Simulations and experimental results confirm the feasibility and the effectiveness of the proposed controller and the advantages of using the dynamic model of the mobile robot. By using this new strategy, the formation of mobile robots is able to change its configuration (shape and size) and follow different trajectories in a precise way, minimizing the tracking and formation errors.

REAL-TIME SLIDING-MODE ADAPTIVE CONTROL OF A MOBILE PLATFORM WHEELED MOBILE ROBOT

This paper presents parameter identification and discrete-time adaptive sliding-mode controller applied to control the mobile platform Pioneer 3-DX wheeled mobile robot (WMR) with 5-DOF manipulator. The dynamic model for mobile robot with two driving wheels, time–varying mass and moment of inertia have been used in sliding-mode control. Two closed-loop, on-line parameter estimators have been used in order to achieve robustness against parameter uncertainties (robot mass and moment of inertia). Two sliding-mode adaptive controllers have been designed corresponding to angular and linear motion. This paper presents closed-loop, circular trajectory tracking real-time control for the mobile robot Pioneer 3-DX.

Verification of a Wheeled Mobile Robot Dynamic Model and Control Ramifications

For low speed, low acceleration, and lightly loaded applications, kinematic models of Wheeled Mobile Robots (WMRs) provide reasonably accurate results. However, as WMRs are designed to perform more demanding, practical applications with high speeds and/or high loads, kinematic models are no longer valid representations. This paper includes experimental results for a heavy, differentially steered WMR for both loaded and unloaded conditions. These results are used to verify a recently developed dynamic model which includes a complex tire representation to accurately account for the tire/ground interaction. The dynamic model is then exercised to clearly show the inadequacy of kinematic models for high load and/or high speed conditions. Furthermore, through simulation, the failure of kinematic model based control for such applications is also shown.