Two-wheeled Mobile Robot Research Articles

Observer-Based Proportional-Type Controller for Two-Wheeled Mobile Robots via Simple Coordinate Transformation Technique

This article briefs on an advanced observer-based proportional-type control scheme that stabilizes the attitude and regulates the position of two-wheeled mobile balancing robots. The robot parameter and load uncertainties are under consideration. There are three main differences from previous results: (a) the development of coordinate transformation for securing the applicability of the proposed nonlinear controller design technique, (b) the pole-zero cancellation parameter-independent observers for estimating the wheel and yaw angular velocities, and (c) the guarantees of performance recovery and offset-free properties through the replacement of integrators via observer-based disturbance observers. The practical merits of the closed-loop analysis are confirmed by performing experiments with a LEGO Mindstorms EV3 operated by MATLAB/Simulink.

Modeling the Kinematics of Two Robots with Denavit–Hartenberg Notation

Abstract This article presents a description and methodology for building a kinematics model for the formation of two-wheeled mobile robots transporting a beam using Denavit–Hartenberg notation. The simple and inverse kinematics tasks of this formation were solved. Solutions of kinematics tasks are presented in junction coordinates and global coordinates. The obtained results were simulated using the Matlab–Simulink package together with animation of the solution using a programmed emulator of robot work.

직렬 탄성 구동기를 이용한 이륜 모바일 로봇의 구현

직렬 탄성 구동기를 이용한 이륜 모바일 로봇의 구현

Optimal Path Tracking With Dubins’ Vehicles

In this article, patrolling with Dubins’ vehicles is investigated. The vehicles have significant kinematic constraints such as minimum-turning radius, and are unable to move in a reverse direction, i.e., they can only track planar curvature-bounded paths. The problem is more challenging than the conventional patrolling problem because the Euclidean traveling salesmen problem (ETSP) solution provides poor estimates of the actual travel time and vehicle location in this case. An algorithm called the pulley algorithm (PA) is developed to convert the ETSP optimal solution to a kinematically feasible optimal Dubins path that can be tracked by Dubins’ vehicles. The PA guarantees that its corresponding optimal path is suitable for patrolling, i.e., for repetitive tracks among the way points. In addition, an upper bound for the PA is presented to show the difference between it and the ETSP optimal solution. This article also introduces enhancements to some of the existing algorithms in the literature in terms of the solution approach. This is followed by practical implementation to control two-wheeled mobile robots using model predictive control to track the Euclidean and the Dubins paths obtained for the patrolling operation.

Kinematic Modeling, Analysis, and Verification of an Essboard-Like Robot

The Essboard is a kind of unusual, portable, two-wheeled vehicle with a special structure and unique locomotion mode. The rider can drive the Essboard easily by twisting the two pedals using both feet. The device may inspire a new type of two-wheeled mobile robots; however, study on this special kind of mobile system is quite inadequate. In this article, we address the kinematics-the most fundamental issue-of an Essboard. The geometric model of the system is first established; then, the holonomic constraints on the two wheels and the holonomic equations are obtained. Finally, the nonholonomic constraints on the system are derived under the condition of pure rolling, and thus the accurate kinematics of the system are established for the first time. To verify the correctness and effectiveness of the established kinematics, a simulation using the virtual prototype technique is conducted, and to reveal its accuracy and advantages, a comparison with the previous model is made. A physical prototype of an Essboard-like robot is developed and employed as a platform to verify the theoretical models. The kinematics built and verified in this article are general and can therefore be applied to other similar monorail vehicles including bicycles and motorcycles.

카메라 기반 이륜 로봇의 라인 추종 및 균형제어

카메라 기반 이륜 로봇의 라인 추종 및 균형제어

Path-Guided Containment Maneuvering of Mobile Robots: Theory and Experiments

This article investigates the path-guided containment maneuvering of networked two-wheeled mobile robots with multiple virtual leaders moving along multiple parameterized paths. A two-level cooperative control architecture is proposed to achieve a containment formation. At the kinematic level, distributed guidance laws and path update laws are developed for mobile robots and virtual leaders, respectively. Containment maneuvering errors are involved in the path update laws design to enforce the coordination between mobile robots and virtual leaders. At the kinetic level, two extended state observers are utilized to estimate the unknown uncertainties existing in surge and yaw dynamics. Then, antidisturbance kinetic control laws are developed through the estimated uncertainties. By using the proposed controllers, the states of mobile robots not only converge to the convex hull spanned by multiple virtual leaders, but also keep a certain formation pattern specified by the convex combination of virtual leaders. The input-to-state stability of the closed-loop path-guided containment maneuvering system is analyzed through Lyapunov theory. The effectiveness of the presented method is verified via experiment on CSICET-MR01 mobile robots.

A traction controller of a two-wheel mobile robot with feedforward compensator

A simple traction controller was derived from a model following control (MFC) using bilinear transformation. The controller was simplified by adjusting some dynamic parameters. The experiments were conducted to evaluate the validity of the controller by comparing with the classical PD controller. In the experiments, while the traction controller can prevent slippage, tracking control performance needed to be improved. The feedforward compensation was added to reduce the traction error. The experimentation using the simple controller with feedforward shows that the position error has been reduced while maintaining the traction force between floor and wheels.

A Mobile Robot Visual SLAM System With Enhanced Semantics Segmentation

Traditional visual simultaneous localization and mapping (SLAM) systems mostly based on small-area static environments. In recent years, some studies focused on combining semantic information with visual SLAM. However, most of them are hard to obtain better performance in the large-scale dynamic environment. And the accuracy, rapidity of the system still needs to strengthen. In this paper, we develop a more efficient semantic SLAM system in the two-wheeled mobile robot by using semantic segmentation to recognize people, chairs, and other objects in every keyframe. With a preliminary understanding of the environment, fusing the RGB-D camera and encoders information, to localization and creating a dense colored octree map without dynamic objects. Besides, for the incomplete identification of movable objects, we used image processing algorithms to enhance the semantic segmentation effect. In the proposed method, enhanced semantic segmentation in keyframes dramatically increases the efficiency of the system. Moreover, fusing the different sensors can highly raise localization accuracy. We conducted experiments on various datasets and in some real environments and compared them with DRE-SLAM, DS-SLAM, to evaluate the performance of the proposed approach. The results suggest we significantly improve the processing efficiency, robustness, and quality of the map.

Control of Two-wheeled Mobile Robots Moving in Formation

Abstract This paper presents control algorithm for multiple non-holonomic mobile robots moving in formation. Method from Canudas et al. (1994) is used to track desired trajectory. In the new algorithm this approach is combined with collision avoidance. Artificial potential functions are used to generate repulsive component of the control. Stability analysis is based on Lyapunov-like function. Effectiveness of the presented method is illustrated by simulation results for a large formation of mobile platforms. Robots avoid collisions with each other and with static obstacles. Position and orientation reach values close to steady state in 50s.

Control Lyapunov Function Design for Trajectory Tracking Problems of Wheeled Mobile Robot

Trajectory tracking is an important control problem that has been studied by many researchers. However, no studies have discussed the trajectory tracking problem for a wheeled mobile robot via the minimum projection method. This paper proposes a Tracking Control Lyapunov Function (TCLF) design that uses dynamic extension and the minimum projection method. The proposed method converges the two-wheeled mobile robot to a time-varying target state. Moreover, the effectiveness of the proposed method is validated through a computer simulation.

Simple discrete time traction control for a two-wheeled mobile robot

Traction controls usually need dynamic parameters as an approximated reference in the model, such as inertia and friction or heavily computational estimator, such as slip ratio estimator and friction estimator. This paper is shown that the dynamic parameters in the traction controller can be negligible in some cases, internal sensor state variables and gain parameters are enough to retain some traction controllability. The controller is derived from the model following control method (MFC) on a discrete domain. Experiments are performed, in order to evaluate the efficiency of the simplified controller using a two-wheeled mobile robot, by comparing slippage between the position and velocity control scheme with and without the traction control scheme. The experimental results show that the proposed traction control scheme is able to suppress the slip and very simple to implement.

Trajectory Generation of a Two-Wheeled Mobile Robot in an Uncertain Environment

This article presents a novel method to generate a trajectory for a two-wheeled mobile robot moving in an uncertain environment where only a few way-points are available to reach a nearby target state. The proposed method interpolates way-points by the combination of a straight line and a fifth-order Bézier curve along which the curvature varies continuously. In addition, a method to generate the associated timing law is proposed such that the robot travels along the curve in near minimum time under the maximum velocity and torque constraints. Since the method aims for an online application, heuristic techniques are applied to minimize the computational cost for finding the optimal solution. The time for computing a complete time-optimal trajectory for a moving robot to transit to a next way-point is only several milliseconds when tested in a personal computer. This result implies that a highly efficient motion control system for a two-wheeled mobile robot can be implemented with a low-cost hardware available today.

Nonlinear Model Predictive Control for Mobile Robot Using Varying-Parameter Convergent Differential Neural Network

The mobile robot kinematic model is a nonlinear affine system, which is constrained by velocity and acceleration limits. Therefore, the traditional control methods may not solve the tracking problem because of the physical constraint. In this paper, we present the nonlinear model predictive control (NMPC) algorithm to track the desired trajectory based on neural-dynamic optimization. In the proposed algorithm, the NMPC scheme utilizes a new neural network named the varying-parameter convergent differential neural network (VPCDNN) which is a Hopfifield-neural network structure with respect to the differential equation theory to solve the quadratic programming (QP) problem. The new network structure converges to the global optimal solution and it is more efficient than traditional numerical methods. In the simulation, we verify that the proposed method is able to successfully track reference trajectories with a two-wheel mobile robot. The experimental validation has been conducted in simulation and the results show that the proposed method is able to precisely track the trajectory maintaining a high robustness based on the VPCDNN solver.

Self-Tuning Position-Tracking Controller for Two-Wheeled Mobile Balancing Robots

This brief proposes an outer-loop control mechanism for two-wheeled mobile balancing robot position-tracking control system applications. The proposed outer-loop controller is comprised of two parts: 1) a simple proportional-type feedback controller and 2) the self-tuning algorithm. The cut-off frequency of closed-loop system is increased by the self-tuning algorithm to enhance the position-tracking performance in transient periods, which is the main contribution of this brief. Moreover, it is rigorously shown that the closed-loop system exponentially recovers the desired position-tracking performance. The closed-loop performance improvement is experimentally verified using the LEGO Mindstorms EV3 with MATLAB/Simulink software.

Trajectory tracking and collision avoidance for the formation of two-wheeled mobile robots

Trajectory tracking and collision avoidance for the formation of two-wheeled mobile robots

A New Approach for Control of Two-wheeled Mobile Robot

In this paper, a study of the GBOT1001 two wheeled mobile robot is presented. Linearized dynamic equations are used to design a controller for the inherently unstable mobile robot. A Fuzzy controller is designed for the robot to direct the orientation of the chassis. Then linear quadratic regulator is also incorporated into the closed-loop system. The parameters of the LQR controller are computed first with the trial and error methods then, with the aid of the Genetic Algorithm. The resulting controller is referred to as the Fuzzy-TE-LQR and Fuzzy-GA-LQR controller respectively. The closed-loop responses for both controllers are obtained via computer simulations. Simulation results show that the Fuzzy-GA-LQR controller exhibits a less oscillatory closed-loop response that is achieved with a reasonable control effort.

Controlling an Underactuated Two-Wheeled Mobile Robot: A Constraint-Following Approach

Controlling underactuated systems is a challenging problem in control engineering. This paper presents a novel constraint-following approach for control design of an underactuated two-wheeled mobile robot (2 WMR), which has two degrees-of-freedom (DOF) to be controlled but only one actuator. The control goal is to drive the 2 WMR to follow a set of constraints, which may be holonomic or nonholonomic constraints. The constraint is considered in a more general form than the previous studies on constraint-following control (hence including a wider range of constraints). No auxiliary variables or pseudo variables are required for the control design. The proposed control only uses physical variables. We show that the proposed control is able to deal with both holonomic and nonholonomic constraints by forcing the constraint-following error to converge to zero, even if the system is not initially on the constraint manifold. Using this control design, we investigate two cases regarding different constraints on the 2 WMR motion, one for a holonomic constraint and the other for a nonholonomic constraint. Simulation results show that the proposed control is able to drive the 2 WMR to follow the constraints in both cases. Furthermore, the standard linear quadratic regulator (LQR) control is applied as a comparison in the simulations, which reflects the advantage of the proposed control.

Event-Triggered Consensus Control for Multiagent Systems With Time-Varying Communication and Event-Detecting Delays

In this paper, using event-triggered control method, we investigate the consensus problem of a distributed single-integrator network with time-varying communication and event-detecting delays. We propose a consensus protocol as well as event-triggering conditions only based on local information. The event-triggering condition for each agent is detected periodically to determine whether its state used in the local feedbacks of the network will be updated or not. A sufficient condition for reaching state consensus is given and the convergence analysis is conducted by Lyapunov methods. The presented result reveals the effect of the change rate of time delays on consensus. Moreover, an experimental example of a multiagent networked system consisting of two-wheeled mobile robots is conducted to demonstrate the feasibility and effectiveness of our proposed consensus protocol.

Supervised control strategy in trajectory tracking for a wheeled mobile robot

In this study, a single input interval type-2 fuzzy logic (SI-IT2-FLC) supervised adaptive neural-fuzzy interface system (ANFIS) controller is proposed for the velocity tracking task of a two-wheeled mobile robot (WMR). The suggested technique can handle the inherent nonlinearities, uncertainties and external disturbances in the system model by a new supervised controller. The robot control design is accomplished by two separate phases including kinematic controller, which is characterized using the kinematic model of the robot, and dynamic controller, which is designed using the physical features of the robot dynamics. In particular, an SI-IT2-fuzzy PD (SI-IT2-FPD) controller is initially applied for the trajectory tracking problem in the two-WMR. In this way, the impact of the footprint of uncertainty (FOU) on control surface (CS) generation is studied, i.e. several CSs were generated by changing a single coefficient which shapes the FOU. Then, a new SI-IT2-FPD supervised ANFIS controller is developed for the concerned robot system. To enhance the efficiency of the suggested controller, the baseline PD gains of the SI-IT2-FPD are adjusted in a heuristic manner. Finally, a prototype of the concerned robot is implemented to investigate the feasibility and applicability of the proposed framework in a real-time platform.