Omnidirectional Mobile Platform Research Articles

Control of a three-wheeled omnidirectional mobile robot via a mixed FTB/$$\mathcal H_\infty $$ approach

AbstractIn this paper, the problem of guidance and motion control of mobile robots is addressed and solved within the novel framework of the mixed finite-time/$$\mathcal H_\infty $$ H ∞ control theory of nonlinear quadratic systems (NLQSs). Starting from a NLQS describing the dynamics of omnidirectional mobile platforms, the main tasks performed for controlling in closed loop the motion of omnidirectional robots can be conveniently formulated as a mixed finite-time/$$\mathcal H_\infty $$ H ∞ control problem. A robust motion controller, which can effectively rejects disturbances deviating the robot platform from a planned path, can be designed after choosing a linear state-feedback structure for the controller. The synthesis problem is solved through some sufficient conditions contemplating both norm-bounded disturbances and sets constraining initial and terminal conditions, together with a finite-time bound on the output transient. Therefore, for all the allowable uncertainties, in presence of nonzero initial conditions and exogenous disturbance inputs which are possible within an unstructured environment, the motion control tasks can be accomplished through optimal $$\mathcal H_\infty $$ H ∞ performance by simultaneously guaranteeing that the NLQS, which governs in closed loop the robot platform, is finite-time bounded. Finally, the applicability and control performance of the design approach have been evaluated through numerical simulations.

Fuzzy Logic-Based Driving Decision for an Omnidirectional Mobile Robot Using a Simulink Dynamic Model

This scientific paper presents the development and validation process of a dynamic model in Simulink used for decision-making regarding the locomotion and driving type of autonomous omnidirectional mobile platforms. Unlike traditional approaches relying on differential equations, this study uses Simulink’s block-based diagrams, offering a simpler and efficient development process. Importantly, the dynamic model accounts for friction forces, a critical factor for energy monitoring. The model’s validation is conducted experimentally, ensuring its accuracy and reliability. This paper formulates mathematical models for both conventional and Mecanum wheel configurations, facilitating energy-efficient driving strategies. By decomposing resistive forces into inertial and frictional components using the Jacobian matrix, this study accurately simulates electrical current consumption during robot motion. Through fuzzy decision algorithms utilizing parameters such as energy consumption, travel time, precision, and desired maneuverability, this paper proposes a method for determining the optimal locomotion mode for mobile platforms with Mecanum wheels. Overall, this research brings a new contribution to the field of mobile robotics by providing a comprehensive framework for dynamic modeling and it offers the possibility to drive omnidirectional robots in an energy-efficient manner.

Multimodal fusion and human-robot interaction control of an intelligent robot.

Introduction: Small-scaled robotic walkers play an increasingly important role in Activity of Daily Living (ADL) assistance in the face of ever-increasing rehab requirements and existing equipment drawbacks. This paper proposes a Rehabilitation Robotic Walker (RRW) for walking assistance and body weight support (BWS) during gait rehabilitation. Methods: The walker provides the patients with weight offloading and guiding force to mimic a series of the physiotherapist's (PT's) movements, and creates a natural, comfortable, and safe environment. This system consists of an omnidirectional mobile platform, a BWS mechanism, and a pelvic brace to smooth the motions of the pelvis. To recognize the human intentions, four force sensors, two joysticks, and one depth-sensing camera were used to monitor the human-machine information, and a multimodal fusion algorithm for intention recognition was proposed to improve the accuracy. Then the system obtained the heading angle E, the pelvic pose F, and the motion vector H via the camera, the force sensors, and the joysticks respectively, classified the intentions with feature extraction and information fusion, and finally outputted the motor speed control through the robot's kinematics. Results: To validate the validity of the algorithm above, a preliminary test with three volunteers was conducted to study the motion control. The results showed that the average error of the integral square error (ISE) was 2.90 and the minimum error was 1.96. Discussion: The results demonstrated the efficiency of the proposed method, and that the system is capable of providing walking assistance.

Fuzzy active disturbance rejection control method for an omnidirectional mobile robot with MY3 wheel

PurposeOmnidirectional mobile robots with a special type of wheel structure can realize flexible motion with all three degrees of freedom in a plane. But the driving method brings large disturbance, which affects motion accuracy and stability. This study aims to improve the motion control accuracy of the omnidirectional mobile platform with MY3 wheels (MY3-OMR), a new fuzzy active disturbance rejection control (FADRC) method with adaptivity is proposed.Design/methodology/approachBased on the basic mechanical structure and drive characteristics of MY3-OMR, the dynamics model of the system is established. The linear active disturbance rejection control (LADRC) system is designed to reduce the interference of nonlinear factors in this dynamics model. A fuzzy controller is introduced to realize the online adjustment of the parameters of the LADRC, which further improves the anti-disturbance performance of the system.FindingsThe control method proposed in this paper is compared and analyzed with other methods by simulation and experiment. Results show that the proposed method has better tracking and robustness, which effectively improves the control accuracy of trajectory tracking of MY3-OMR.Originality/valueA FADRC method with adaptivity is proposed by combining fuzzy control and LADRC. The motion accuracy and anti-interference ability of the MY3-OMR are improved by this control method, which lays a foundation for the subsequent application of MY3-OMR.

Simulation study on assist-as-needed control of a rehabilitation robotic walker.

Along with China entering an aging society, the percentage of people that over 60 will reach 34.9% in 2050, resulted in a significant increase in stroke patients. This paper proposes a rehabilitation robotic walker for walking assistance during the daily life, and a control method for the motor relearning during the gait training. The walker consists of an omni-directional mobile platform (OMP) which ensures the walker can move on the ground, a body weight support system (BWS) which is capable of providing the desired unloading force, and a pelvic assist mechanism (PAM) to provide the user with four degrees of freedom and avoid the rigid impact. The study goal is to gain a better understanding of the assist-as-needed control strategy during the gait training. For the man-machine interaction control, the assist-as-needed control strategy is adopted to guide the users' motions and improve the interaction experience. To build the force field in the three-dimensional space, the dynamics of the system is derived to increase the accuracy of force control. The simulation results show that the force field around the motion trajectory was generated in the three-dimensional space. In order to understand the force field, we designed the simulation on sagittal plane and the controller can generate the appropriate force field. The preliminary experiment results were consistent with the simulation results. Based on the mathematical simulation and the preliminary test, the results demonstrate that the proposed system can provide the guide force around the target trajectory, the accuracy of force control still remains to be improved.

Design and Motion Control of Spherical Robot With Built-In Four-Wheel Omnidirectional Mobile Platform

The objective of this paper is to propose a novel spherical robot with built-in four-wheel omnidirectional mobile platform. The employment of four-wheel structure helps to improve the friction coefficient and thus reduce the slipping motion. In addition, it increases the velocity augmentation factor, and thus compensation methods can be effectively implemented into the system to decrease the slipping motion further. Moreover, the traction force is increased and thus the loading capacity can be improved correspondingly. First, the schematic structure along with the operating principle of the proposed spherical robot is introduced. Then, the kinematic and dynamic models are formulated analytically. The slipping error between the omnidirectional wheels and the inner wall of the sphere is analyzed. The slip observer and the motion controller are designed, and their convergence is proved theoretically. Subsequently, simulation is conducted to validate the proposed slip observer that is in turn implemented into the motion controller. The trajectory tracking of the spherical robot on straight line and circle is verified. Following that, one research prototype of the spherical robot with built-in four-wheel omnidirectional mobile platform is developed. Experimental investigation shows that the research prototype embedded with the slip observer can achieve the trajectory tracking performance very well.

Kinematics and Trajectory Planning of the Masonry Robot

Abstract This paper proposes a mechanical system for a masonry robot comprising four parts: an omnidirectional mobile platform, a lifting platform, a six-degrees-of-freedom manipulator, and a grasping mechanism. The robot is specifically designed to carry out brick masonry on construction sites and is equipped to move bricks smoothly with slurry to their intended location. To prevent mortar from being shaken off the brick, the grasping mechanism is required to maintain optimal velocity and optimized acceleration. To implement online trajectory planning with velocity and acceleration constraints, the paper suggests an approach based on screw theory for resolving the inverse kinematics of the masonry robot. This method allows the inverse kinematic equations to be used to determine a unique solution for all joints of the redundant driver of the masonry robot. The approach and strategy are validated through numerical simulations of trajectory planning using a fifth-degree polynomial.

A GNN for repetitive motion generation of four-wheel omnidirectional mobile manipulator with nonconvex bound constraints

This paper proposes a gradient neural network (GNN) to solve the repetitive motion generation scheme of the omnidirectional four-wheel mobile manipulator. The overall kinematics model of the omnidirectional mobile platform and the manipulator fixed on omnidirectional platform are established. First, the analysis of the current repetitive movement generation (RMG) scheme for the kinematic control of the manipulator can find that the position error does not theoretically converge to zero and fluctuates. This paper analyzes the phenomenon from a theoretical viewpoint and reveals that the current RMG scheme has position errors associated with joint errors. Then, to solve the shortcomings of the current solution, an orthogonal projection repetitive motion generation (OPRMG) method is proposed, which theoretically eliminates position errors and decouples joint space and Cartesian space. Using the gradient descent method to establish the corresponding GNN aided with the speed compensation, and provide theoretical analysis to reflect the stability. Moreover, the joint speed limit in the RMG scheme is extended to nonconvex constraints. The advantages of the OPRMG scheme are demonstrated by the simulation results of the omnidirectional mobile manipulator (OMM) synthesized by the current GNNRMG and the proposed GNNOPRMG. In addition, by adjusting the feedback coefficient, the high performance of the OPRMG scheme can be verified by simulation and comparison of the position error (PE) and joint error (JE) of the OMM.

Intelligent assistance for older adults via an admittance-controlled wheeled mobile manipulator with task-dependent end-effectors

The increase in the ageing population worldwide poses a severe challenge in assisting older individuals to live independently, including the provision of mobility assistance and support in daily activities. In this paper, a practical robotic system is developed to provide intelligent support for older persons using a wheeled mobile manipulator (WMM), consisting of an omnidirectional mobile platform and a robotic arm. We focus on two critical needs: (1) mobility assistance, and (2) object manipulation support. The tasks are not executed simultaneously and each uses a task-dependent end-effector. Learning from demonstration, or kinesthetic teaching, is adopted to help the WMM to learn an elderly or disabled user’s walking pattern or an able-bodied person’s object manipulation skill. The robotic system can assist the user in conducting a number of daily operations. For mobility assistance, the WMM is reconfigured into a smart walker, where a novel variable admittance control is adopted to detect the user’s walking intention. A learning approach based on dynamic movement primitives is implemented to capture and adapt the WMM to the user’s walking pattern. For object manipulation support, a demonstrator first collaborates with an elderly user to conduct the task, and then the WMM takes the role of the demonstrator to assist the user. The Gaussian mixture model and Gaussian mixture regression are used to learn and reproduce the demonstrator’s experience, respectively. The advantages and effectiveness of the proposed approach are experimentally demonstrated with a four-wheel omnidirectional WMM.

Motion optimization of an omnidirectional mobile robot with MY wheel based on contact mechanics

PurposeThe mechanical properties between wheel and ground will affect the motion performance of wheeled omnidirectional mobile robot (OMR). MY3 wheel is an omnidirectional wheel. This paper aims to analyze the contact mechanical characteristics between MY3 wheel and ground to improve the motion accuracy of an omnidirectional mobile platform with MY3 wheel (MY3-OMR).Design/methodology/approachThis method takes MY3 wheel as the research objective. The normal and tangential contact mechanics model and rolling contact mechanics model of MY3 wheel are established by analyzing the structure of MY3 wheel, and thereby, the slip ratio of MY3 wheel in the process of motion is calculated. The kinematics model of MY3-OMR is optimized by taking the slip ratio as the optimization parameter that aims to improve motion accuracy of MY3-OMR.FindingsThe correctness of the mechanical analysis and the feasibility of the method are verified by the MY3-OMR prototype. Let MY3-OMR move along the set circular trajectory and square trajectory, and the error between the motion trajectory before and after optimization and the standard trajectory is obtained. It illustrates that the error in the square trajectory is reduced by 1.5%, and the circular trajectory error is reduced by 2%; therefore, the method is effective.Originality/valueA method based on contact mechanics is proposed and verified. Through the establishment of wheel-ground contact mechanics model to optimize MY3-OMR kinematics model, and thereby, the motion accuracy of MY3-OMR is improved, which lays a foundation for MY3-OMR engineering application.

Kinematic and dynamic analysis of an omnidirectional mobile platform driven by a spherical wheel

Abstract. The increased use of spherical wheels has allowed mobile robots to have a higher degree of maneuverability, less complex path planning and less complex control schemes. The geometry and design of the mobile robot are the principal attributes that guarantee an omnidirectional motion. Furthermore, the platform uses an active spherical wheel and four passive spherical wheels to get the best stability when the robot uses a terminal element (Kärcher). The proposed model has been designed to improve the omnidirectional motion issues, such as vibration into the platform or lack of punctual contact between the wheel and the floor, compared to mobile robots using Mecanum wheels and more than one active wheel; due to the design concept, all the mathematical formulations, kinematics and dynamics presents how the models are validated with computer simulations.

Paquitop.arm, a Mobile Manipulator for Assessing Emerging Challenges in the COVID-19 Pandemic Scenario

The use of automation and robotics technologies for caregiving and assistance has become a very interesting research topic in the field of robotics. The spread of COVID-19 has highlighted the importance of social distancing in hospitals and health centers, and collaborative robotics can bring substantial improvements in terms of sparing health workers basic operations. Thus, researchers from Politecnico di Torino are working on Paquitop.arm, a mobile robot for assistive tasks. The purpose of this paper is to present a system composed of an omnidirectional mobile platform, a 6 DOF robot arm, and a depth camera. Task-oriented considerations are made to estimate a set of mounting parameters that represents a trade-off between the exploitation of the robot arm workspace and the compactness of the entire system. To this end, dexterity and force transmission indexes are introduced to study both the kinematic and the static behavior of the manipulator as a function of the mounting parameters. Finally, to avoid singularities during the execution of the task, the platform approach to the task workspaces is studied.

PID control of an omnidirectional mobile platform based on an RBF neural network controller

PurposeOmnidirectional mobile platforms are still plagued by the problem of heading deviation. In four-Mecanum-wheel systems, this problem arises from the phenomena of dynamic imbalance and slip of the Mecanum wheels while driving. The purpose of this paper is to analyze the mechanism of omnidirectional motion using Mecanum wheels, with the aim of enhancing the heading precision. A proportional-integral-derivative (PID) setting control algorithm based on a radial basis function (RBF) neural network model is introduced.Design/methodology/approachIn this study, the mechanism of omnidirectional motion using Mecanum wheels is analyzed, with the aim of enhancing the heading precision. A PID setting control algorithm based on an RBF neural network model is introduced. The algorithm is based on a kinematics model for an omnidirectional mobile platform and corrects the driving heading in real time. In this algorithm, the neural network RBF NN2 is used for identifying the state of the system, calculating the Jacobian information of the system and transmitting information to the neural network RBF NN1.FindingsThe network RBF NN1 calculates the deviations ?Kp, ?Ki and ?Kd to regulate the three coefficients Kp, Ki and Kd of the heading angle PID controller. This corrects the driving heading in real time, resolving the problems of low heading precision and unstable driving. The experimental data indicate that, for a externally imposed deviation in the heading angle of between 34º and ∼38°, the correction time for an omnidirectional mobile platform applying the algorithm during longitudinal driving is reduced by 1.4 s compared with the traditional PID control algorithm, while the overshoot angle is reduced by 7.4°; for lateral driving, the correction time is reduced by 1.4 s and the overshoot angle is reduced by 4.2°.Originality/valueIn this study, the mechanism of omnidirectional motion using Mecanum wheels is analyzed, with the aim of enhancing the heading precision. A PID setting control algorithm based on an RBF neural network model is introduced. The algorithm is based on a kinematics model for an omnidirectional mobile platform and corrects the driving heading in real time. In this algorithm, the neural network RBF NN2 is used for identifying the state of the system, calculating the Jacobian information of the system and transmitting information to the neural network RBF NN1. The method is innovative.

A non-cooperative game approach to the robust control design for a class of fuzzy dynamical systems

Aiming at the time-varying bounded uncertainty in the mechanical system and the problem of excessive control gain caused by the “worst case”, a robust control with tunable parameters that can be used to compensate for the uncertainty is proposed. The proposed control can guarantee that the system has uniform boundedness and uniform ultimate boundedness. Besides, the fuzzy set theory is used to describe the uncertainty to avoid introducing any IF-THEN fuzzy logic rules or probability theory. Based on the non-cooperative game theory, the parameters of the proposed control are optimized. We treat mutually independent parameters to be optimized as players, then design performance indexes for each parameter as its cost function, and solve the optimal result by the definition of Nash equilibrium. Finally, taking the trajectory tracking control of omnidirectional mobile platform as an example, the feasibility of the optimization method and the effectiveness of the control are verified by comparing with the other two control methods.

Two-Vehicle Coordination System for Omnidirectional Transportation Based on Image Processing and Deviation Prediction

Omnidirectional mobile platform is essential due to its excellent mobility and versatility. With the development of the manufacturing industry, how to transport oversized or overweight goods has become a new problem. Compared with manufacturing omnidirectional mobile platforms with different specifications, it is more cost-effective and flexible to coordinate two non-physically connected omnidirectional platforms to transport overweight and oversized cargo. The roughness of the actual deployment environment and the mechanical deflection between the two vehicles have a significant impact on the normal operation of the system. This paper combines mechanical wheels, image processing algorithms and collaboration algorithms to create a novel and practical split-type omnidirectional mobile platform based on image deviation prediction for transporting oversized or overweighted goods. The proposed system collects raw measurements from a distance sensor and an image sensor, transmits them to a central processing unit through a wireless communication module and calculates and predicts the relative deflection between the two vehicles based on our derived mathematical model. This information is then fed to a Kalman filter and PID control algorithm to coordinate the two vehicles. The effectiveness and performance of our system have been thoroughly tested, which has already been applied in a bullet train production line.

Omnidirectional Platforms for Gait Training: Admittance-Shaping Control for Enhanced Mobility

We present a design method for the admittance control of a class of omnidirectional mobile platforms. Holonomic behavior of the platform is accomplished by a steering system that is itself subject to nonholonomic constraints. The proposed application of this type of platform, henceforth the “walker”, is as an assistive device for human gait rehabilitation. Therefore, the control design objectives are to guarantee the stability of the coupled system formed by the robotic platform and the human body, and to maximize mobility for the user by reducing the robot’s apparent inertia. First, we show how feedback linearization of a reduced-order model of the system, combined with a smooth trajectory-tracking control, achieves global asymptotic stability of the tracking error. Then we show how compliance in the robot limits the amount of inertia reduction that can be achieved before instability occurs. We address this problem with a control design method that maximizes the amplitude of the system’s admittance over a useful range of frequencies. Using root locus analysis and sensitivity transfer functions, we find an optimal value for the virtual mass in the admittance model, representing the best tradeoff between two oscillatory modes. The walker’s admittance vs. frequency function is then corrected via a complementary sensor input, namely, the user’s torque on the sagittal plane. A second layer of control provides the walker’s therapeutic action, consisting of a variable horizontal force that aids propulsion of the user’s body. The level of assistive force is modulated with the patient’s gait speed and turning rate to ensure easy adaptation. The control design was validated through an experiment involving human users walking in a prototype of the mobile platform.

A novel algorithm based on nonlinear optimization for parameters calibration of wheeled robot mobile chasses

Mobile robot positioning, mapping, and navigation systems generally employ an inertial measurement unit to obtain the acceleration and angular velocity of the robot. However, errors in the internal and external parameters of an inertial measurement unit arising from defective calibration directly affect the accuracy of robot positioning and pose estimation. While this issue has been addressed by the mature internal parameters calibration method available for inertial measurement unit, external reference calibration method between the inertial measurement unit and the chassis of a mobile robot are lacking. This study addresses this issue by proposing a novel algorithm for internal parameter calibration of mecanum wheel omnidirectional mobile platform and external parameter calibration of mecanum chassis- inertial measurement unit based on principal component analysis and nonlinear optimization, which is designed for robots equipped with cameras, inertial measurement unit, mecanum wheels, and wheel speed odometers, and functions under the premise of accurate calibrations for the internal parameters of the inertial measurement unit and the internal and external parameters of the camera. All of the internal and external parameters calibrations are conducted using the robot's existing equipment without the need for additional calibration aids. The feasibility of the method is verified by its application to a mecanum wheel omnidirectional mobile platform. The proposed calibration method is thereby demonstrated to guarantee the accuracy of robot pose estimation.

Research on Trajectory Tracking Control Method of Omnidirectional Moving Platform Based on Backstepping

According to the relevant theoretical methods of omnidirectional mobile mechanism, the kinematic model of omnidirectional mobile platform under theoretical conditions is established, and the dynamic model of omnidirectional mobile mechanism in actual environment is analyzed according to the specific situation of platform body structure and actual influencing factors. Based on the kinematic model, a backstepping based trajectory tracking control method for omnidirectional mobile platform is designed, and the trajectory tracking error equation is solved. In order to further improve the stability of the system, a fuzzy control system based on backstepping method is designed based on the dynamic model, and the control torque of the platform is selected. Finally, the effectiveness of this method is verified by numerical simulation.

Design and Research of Intelligent Logistics Robot based on STM32

Background: At present, China's logistics industry is trying to change from laborintensive to technology-intensive, from the traditional model to modernization, intelligent upgrade, accompanied by the application and popularization of various advanced technologies and equipment. Nowadays, intelligent robots with functions such as handling, stacking, and sorting have become a hot topic in the logistics industry. To solve the problem of labor costs increase the logistics demand of logistics, improve the efficiency of processing of materials, the authors have designed main STM32F427 microcontroller chip, with smooth, round of omnidirectional mobile platform of vehicle chassis, external collision distance sensor, gyroscope and infrared sensors, temporary storage, and transportation of goods such as multi-functional integrated logistics robot. Methods: According to the actual application requirements, the mechanical structure of the logistics robot, the hardware, and the software of the control system is designed. Results: The experimental results show that the transportation and storage of materials in specific sites are well realized. The grasping and releasing accuracy and the positioning accuracy of the robot are relatively reliable. The study of the behavior of average tracking accuracy and average obstacle avoiding capability is the major contribution in this paper. Conclusion: The experimental results fully prove that the robot designed in this paper has many functions, high intelligence, and strong practicability.

Research of Intelligent Temperature Measuring Robot System

With the outbreak of novel coronavirus pneumonia worldwide, a kind of epidemic prevention robot is urgently needed in society. The intelligent temperature measurement robot system mainly includes the robot’s high stability multi-attitude omnidirectional movement module, robot path planning and autonomous navigation module, robot environment information acquisition and recognition module, robot remote control module, and robot system integration. According to the design principle of the wheeled robot, high stability and multi attitude omni-directional mobile platform of temperature measuring robot are constructed; path planning and autonomous navigation of robot are realized based on sensor data fusion; temperature detection and remote care function are realized by thermal imaging sensor system by capturing the thermal radiation emitted by the human body, and based on open modular control system architecture. Based on the existing research foundation, the intelligent temperature measurement robot system is established by integrating the robot multi attitude omni-directional mobile system, robot path planning, and autonomous navigation system, robot environment information acquisition and recognition system, and robot remote control system.