Two-wheeled Mobile Robot Research Articles

Output Feedback Tracking Control of Flat Systems via Exact Feedforward Linearization and LPV Techniques

In this article, an output feedback control scheme is proposed for trajectory tracking of differentially flat systems. After applying the exact feedforward linearization, the tracking error dynamics is linearized as a linear time-varying (LTV) system, where only the state matrix is time-varying while the input and output matrices are time-invariant. Using linear parameter-varying (LPV) techniques based on polytopes, for the LTV system the controller matrices, which are set to be affine on time-varying parameters, are calculated by solving a set of linear matrix inequalities (LMIs). An example for trajectory tracking of a two-wheeled mobile robot is given to show the effectiveness of the proposed method.

Same Fuzzy Logic Controller for Two-Wheeled Mobile Robot Navigation in Strange Environments

For any mobile device, the ability to navigate smoothly in its environment is of paramount importance, which justifies researchers’ continuous work on designing new techniques to reach this goal. In this work, we briefly present a description of a hard work on designing a Same Fuzzy Logic Controller (S.F.L.C.) of the two reactive behaviors of the mobile robot, namely, “go to goal obstacle avoidance” and “wall following,” in order to solve its navigation problems. This new technique allows an optimal motion planning in terms of path length and travelling time; it is meant to avoid collisions with convex and concave obstacles and to achieve the shortest path followed by the mobile robot. The efficiency of employing the proposed navigational controller is validated when compared to the results from other intelligent approaches; its qualities make of it an efficient alternative method for solving the path planning problem of the mobile robot.

Development of Smart Trolley System Based on Android Smartphone Sensors

In supermarkets, a shopping trolley or a shopping cart is the necessary tools for purchasing. Traditionally, it is used by customers inside the store to transport goods to the cashier during shopping and designed not to leave the store. It is an inconvenience and time wasted for customers who want to find the desired product in the store by using the traditional shopping trolley. Our goal is to develop an automatic moving trolley with smart shopping devices to solve the problem. Our smart shopping trolley is based on a two-wheeled mobile robot, developed in our previous research. This paper presents the hardware and software design of a smart trolley system. Our smart trolley used IOIO microcontroller and Android smartphone as sensors and controller. The trolley is modeled as a two-wheeled mobile robot. Android smartphone will control the robot by sending a signal to IOIO microcontroller paired with a robot’s actuator and monitor the situation using the smartphone camera. Furthermore, we exploited the smartphone compass for robot navigation. This system is also equipped with the indoor positioning system to detect user position using Navisens which based on gyroscope and accelerometer in the smartphone. Finally, the results of the testing on robot navigation are presented. The result is our smart trolley system based on Navisens framework can move and show its location to the user.

Inverted two-wheel jumping mobile robot with active suspension and jumping movement function

Inverted two-wheel jumping mobile robot with active suspension and jumping movement function

Driving control of Low Center of Gravity Typed Two-Wheeled Mobile Robot for Tour Guide

Driving control of Low Center of Gravity Typed Two-Wheeled Mobile Robot for Tour Guide

Design and Mobility Analysis of a Multi-mode Two-wheel Mobile Robot

Design and Mobility Analysis of a Multi-mode Two-wheel Mobile Robot

Movement control of two-wheeled mobile robots by image processing

Movement control of two-wheeled mobile robots by image processing

Development and analysis of DAYANI arc contour intelligent technique for navigation of two-wheeled mobile robot

Purpose This paper aims to generate an obstacle free real time optimal path in a cluttered environment for a two-wheeled mobile robot (TWMR). Design/methodology/approach This TWMR resembles an inverted pendulum having an intermediate body mounted on a robotic mobile platform with two wheels driven by two DC motors separately. In this article, a novel motion planning strategy named as DAYANI arc contour intelligent technique has been proposed for navigation of the two-wheeled self-balancing robot in a global environment populated by obstacles. The developed new path planning algorithm evaluates the best next feasible point of motion considering five weight functions from an arc contour depending upon five separate navigational parameters. Findings Authenticity of the proposed navigational algorithm has been demonstrated by computing the path length and time taken through a series of simulations and experimental verifications and the average percentage of error is found to be about 6%. Practical implications This robot dynamically stabilizes itself with taller configuration, can spin on the spot and rove along through obstacles with smaller footprints. This diversifies its areas of application to both indoor and outdoor environments especially with very narrow spaces, sharp turns and inclined surfaces where its multi-wheel counterparts feel difficult to perform. Originality/value A new obstacle avoidance and path planning algorithm through incremental step advancement by evaluating the best next feasible point of motion has been established and verified through both experiment and simulation.

Modeling and trajectory tracking control of a two-wheeled mobile robot: Gibbs–Appell and prediction-based approaches

SUMMARYThis study deals with the problem of trajectory tracking of wheeled mobile robots (WMR's) under non-holonomic constraints and in the presence of model uncertainties. To solve this problem, the kinematic and dynamic models of a WMR are first derived by applying the recursive Gibbs–Appell method. Then, new kinematics- and dynamics-based multivariable controllers are analytically developed by using the predictive control approach. The control laws are optimally derived by minimizing a pointwise quadratic cost function for the predicted tracking errors of the WMR. The main feature of the obtained closed-form control laws is that online optimization is not needed for their implementation. The prediction time, as a free parameter in the control laws, makes it possible to achieve a compromise between tracking accuracy and implementable control inputs. Finally, the performance of the proposed controller is compared with that of a sliding mode controller, reported in the literature, through simulations of some trajectory tracking maneuvers.

Event-Based Rendezvous Control for a Group of Robots With Asynchronous Periodic Detection and Communication Time Delays.

In this paper, we propose an event-triggered rendezvous control method for multiple two-wheeled mobile robots (2WMRs) subject to time-varying communication delays. By checking the integral-type event-triggering conditions asynchronously and periodically, each 2WMR determines whether or not to sample and broadcast its states. When the information used in an agent's controller is updated, the 2WMR calculates its x (or y ) control input, and then a Rotate&Compensate&Run Rendezvous Scheme is provided for 2WMRs to update their states. We present a sufficient condition for 2WMRs to asymptotically reach rendezvous, and the convergence analysis is conducted using the Lyapunov functional approach. Experiments are further presented to validate the effectiveness of the proposed control method.

Rapid Navigation Function Control for Two-Wheeled Mobile Robots

This paper presents a kinematic controller for a differentially driven mobile robot. The controller is based on the navigation function (NF) concept that guarantees goal achievement from almost all initial states. Slow convergence in some cases is a significant disadvantage of this approach, especially when narrow passages exist in the environment and/or specific values of design parameters are set. The main reason of this phenomenon is that the velocity control strongly depends on the slope of the NF. The algorithm proposed in this paper is based on a method introduced in Urakubo (Nonlin. Dyn. 81(3): 1475–1487 2015), that extends NF to nonholonomic mobile platforms and allows stabilizing not only the position of robots but also their orientation. This algorithm is used as a reference in experimental performance comparison. In the new algorithm, the gradient of the NF is used to generate motion direction but the velocity is computed as a function of position and orientation errors. This approach results in much better state converge. Analysis of the convergence shows how the location of the eigenvalues of linearized system affects time of goal achievement. The paper describes saddle point detection and avoidance methodology and presents their experimental verification. It also shows what happens in practice if initial position is located exactly in the saddle point and its detection/avoidance procedures are turned off.

이륜로봇과 드론의 합체를 위한 연결부 설계 및 합체 시스템의 균형 및 주행 제어

이륜로봇과 드론의 합체를 위한 연결부 설계 및 합체 시스템의 균형 및 주행 제어

Development of a self-balancing robot with a control moment gyroscope

This study introduces a two-wheeled self-balancing mobile robot based on a control moment gyroscope module. Two-wheeled mobile robots are able to achieve better mobility and rotation in small space...

Trajectory-tracking Sliding Mode Control for Two-Wheeled Mobile Robot

According to the mechanical structure and operation principle of differential-drive two-wheeled robot, and aiming at the nonlinear systems with uncertainties variable structure, a trajectory tracking model based on sliding mode control (SMC) was designed by utilizing state vector to establish the model of system and controller. The simulating results show that robot can track line, circle and S shape trajectories well, which gave reasonable dynamic responses, adjustment performance, as well as perfect disturbance rejection. The system can eliminate errors according to the deviation from sliding surface by switching the structure of controller and is robust to external disturbance.

Distributed LQR Consensus Control for Heterogeneous Multiagent Systems: Theory and Experiments

Controlling heterogeneous multiagent systems (MASs) to cooperatively accomplish tasks is currently an emerging topic in the application-oriented research of robotics. This paper investigates the consensus problem of a MAS consisting of quadrotors and two-wheeled mobile robots (2WMRs). Directed and switching interaction topologies over the network are considered. We propose a distributed linear quadratic regulation (LQR) consensus protocol for the quadrotors and design an LQR-based Rotate&Run Consensus Scheme for the 2WMRs to update the states. We use the algebraic graph theory and stochastic matrix analysis to conduct the convergence analysis of consensus. The underactuation characteristic of the 2WMR dynamics is considered in the controller design. The effectiveness of the control methods is verified by simulations and experiments.

A sub-target approach to the kinodynamic motion control of a wheeled mobile robot

A mobile robot with two independently driven wheels is popular, but it is difficult to stabilize it by a continuous controller with a constant gain, due to its nonholonomic property. It is guaranteed that a nonholonomic controlled object can always be converged to an arbitrary point using a switching control method or a quasi-continuous control method based on an invariant manifold in a chained form. From this, the authors already proposed a kinodynamic controller to converge the states of such a two-wheeled mobile robot to the arbitrary target position while avoiding obstacles, by combining the control based on the invariant manifold and the harmonic potential field (HPF). On the other hand, it was confirmed in the previous research that there is a case that the robot cannot avoid the obstacle because there is no enough space to converge the current state to the target state. In this paper, we propose a method that divides the final target position into some sub-target positions and moves the robot step by step, and it is confirmed by the simulation that the robot can converge to the target position while avoiding obstacles using the proposed method.

Nonlinear reduced dynamics modelling and simulation of two-wheeled self-balancing mobile robot: SEGWAY system

ABSTRACTSegway is a self-balancing motorized two-wheeled vehicle which is able to carry the human body. In the presented paper, a problem of nonholonomic constrained mechanical systems is treated. New methods in nonholonomic mechanics are applied to a problem of a two-wheeled self-balancing robots motion ‘SEGWAY’. This method of the geometrical theory of general nonholonomic constrained systems on fibred manifolds and their jet prolongations, based on so-called Chetaev-type constraint forces, was proposed and developed in the last decade by Krupková and others. The equations of motion of a two-wheeled self-balancing robot are highly nonlinear and rolling without slipping condition can only be expressed by nonholonomic constraint equations. In this paper, the geometrical theory is applied to the above mentioned mechanical problem using the above mentioned Krupková approach. Additionally, the results of numerical solutions of constrained equations of motion derived within the theory are in good agreement with results of (1) [Maddahi, A., Shamekhi, A. H., & Ghaffari, A. (2015). A Lyapunov controller for self-balancing two-wheeled vehicles. Robotica, 33(1), 225–239]. using Lyapunov's feedback control design technique. The existence, continuity, and uniqueness of the solution for the proposed control system are proved utilizing the Filippov's solution (2). And with fuzzy controller proposed by [Qian, Q., Wu, J., & Wang, Z. (2017). A novel configuration of two-wheeled self-balancing robot/Nova konfiguracija samobalansirajuceg robota na dva kotaca (Original scientific paper/Izvorni znastveni clanak). Tehnicki Vjesnik-Technical Gazette, 24(2), 459–465].

Integral Sliding Mode Flight Controller Design for a Quadrotor and the Application in a Heterogeneous Multi-Agent System

This paper investigates a novel integral sliding mode control (ISMC) strategy for the waypoint tracking control of a quadrotor in the presence of model uncertainties and external disturbances. The proposed controller has the inner–outer loop structure: The outer loop is to generate the reference signals of the roll and pitch angles, while the inner loop is designed by using the ISMC technique for the quadrotor to track the desired $x$ , $y$ positions and roll and pitch angles. The Lyapunov stability analysis is provided to show that the negative effects of the bounded model uncertainties and external disturbances can be significantly decreased. The designed controller is then applied to a heterogeneous multi-agent system (MAS) consisting of quadrotors and two-wheeled mobile robots (2WMRs) to solve the consensus problem. We present the control algorithms for the 2WMRs and quadrotors. Consensus of the heterogeneous MAS can be reached if the switching graphs always have a spanning tree. Finally, the experimental tests are conducted to verify the effectiveness of the proposed control methods.

Open-Source Hardware를 이용한 이동 로봇의 실시간 경로 추종 제어의 구현

In this paper, we propose an implementation method of the real-time tracking control system for a two-wheeled mobile robot. The proposed tracking control system is structured so that the target velocities are generated using the reference generated by the realtime path generator and current posture information of the robot. Two PI controllers are used to track he target velocities. The proposed realtime path generator generates SPP (single polar polynomial) curves for the curved path and can handle the speed and acceleration constraints of the actuators of the mobile robot. The proposed path generator does not need to store the entire path information over time. It computes and saves the minimum information required to generate the path offline and generates all path references in real-time. The proposed method is implemented in Arduino Due, which is an open source hardware, and applied to a lab-built mobile to demonstrate that the proposed tracking control system can be implemented on a small scale system such as a microcontroller.

Experimental Study on Behavior Acquisition of Mobile Robot by Deep Q-Network

Deep Q-network (DQN) is one of the most famous methods of deep reinforcement learning. DQN approximates the action-value function using Convolutional Neural Network (CNN) and updates it using Q-learning. In this study, we applied DQN to robot behavior learning in a simulation environment. We constructed the simulation environment for a two-wheeled mobile robot using the robot simulation software, Webots. The mobile robot acquired good behavior such as avoiding walls and moving along a center line by learning from high-dimensional visual information supplied as input data. We propose a method that reuses the best target network so far when the learning performance suddenly falls. Moreover, we incorporate Profit Sharing method into DQN in order to accelerate learning. Through the simulation experiment, we confirmed that our method is effective.