Three-wheeled Omnidirectional Mobile Robot 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.

Trajectory tracking control of a three-wheeled omnidirectional mobile robot using disturbance estimation compensator by RBF neural network

Trajectory tracking control of a three-wheeled omnidirectional mobile robot using disturbance estimation compensator by RBF neural network

English

This paper presents the research and construction of a motion tracing control system for omnidirectional mobile robots based on reinforcement learning techniques in automatic control. The process of controlling a mobile robot in a flat environment with definite and unknown obstacles, taking into account the nonlinear factor of interference. Research and application of programming tools are operating systems for mobile robots (Robot Operating System - ROS). From updated information on maps, operating environment, robot control position, and obstacle identification (SLAM) to calculate the movement trajectory of a three-wheeled omnidirectional mobile robot. The positioning system calculates the orbital tracking for the robot based on the Q-learning algorithm. The results of simulation research in the Gazebo environment and running tests on real Turtlebot mobile robots have shown the practical effectiveness of the research problem of tracking motion tracking and intelligent navigation for mobile robots.

Non-Parametric Calibration of the Inverse Kinematic Matrix of a Three-Wheeled Omnidirectional Mobile Robot Based on Genetic Algorithms

Odometry is a computation method that provides a periodic estimation of the relative displacements performed by a mobile robot based on its inverse kinematic matrix, its previous orientation and position, and the estimation of the angular rotational velocity of its driving wheels. Odometry is cumulatively updated from tens to hundreds of times per second, so any inaccuracy in the definition of the inverse kinematic matrix of a robot leads to systematic trajectory errors. This paper proposes a non-parametric calibration of the inverse kinematic (IK) matrix of a three-wheeled omnidirectional mobile robot based on the use of genetic algorithms (GA) to minimize the positioning error registered in a set of calibration trajectories. The application of this non-parametric procedure has provided an average improvement of 82% in the estimation of the final position and orientation of the mobile robot. This is similar to the improvement achieved with analogous parametric methods. The advantage of this non-parametric approach is that it covers a larger search space because it eliminates the need to define feasible physical limits to the search performed to calibrate the inverse kinematic matrix of the mobile robot.

Tracking a Mobile Robot in a UWB-sensor Grid

This work presents the development of a tracking system for a three-wheeled omnidirectional mobile robot. This kind of robot can perform rotation and translation in any pose. The arc-length segment described by the omni-wheels controls the trajectory of the robot. We present a simplified kinematic model in state-space. The observation system is based on an UltraWide Band ranging sensor. Finally made the state estimation using some classic positioning algorithms and compare the results against Finite Impulse Response Filter state estimators.

Systematic Odometry Error Evaluation and Correction in a Human-Sized Three-Wheeled Omnidirectional Mobile Robot Using Flower-Shaped Calibration Trajectories

Odometry is a simple and practical method that provides a periodic real-time estimation of the relative displacement of a mobile robot based on the measurement of the angular rotational speed of its wheels. The main disadvantage of odometry is its unbounded accumulation of errors, a factor that reduces the accuracy of the estimation of the absolute position and orientation of a mobile robot. This paper proposes a general procedure to evaluate and correct the systematic odometry errors of a human-sized three-wheeled omnidirectional mobile robot designed as a versatile personal assistant tool. The correction procedure is based on the definition of 36 individual calibration trajectories which together depict a flower-shaped figure, on the measurement of the odometry and ground truth trajectory of each calibration trajectory, and on the application of several strategies to iteratively adjust the effective value of the kinematic parameters of the mobile robot in order to match the estimated final position from these two trajectories. The results have shown an average improvement of 82.14% in the estimation of the final position and orientation of the mobile robot. Therefore, these results can be used for odometry calibration during the manufacturing of human-sized three-wheeled omnidirectional mobile robots.

Digital Twinning for Closed-Loop Control of a Three-Wheeled Omnidirectional Mobile Robot

Mobile robots are becoming increasingly important in industrial and technological applications. One of the most important characteristics of an autonomous mobile robot is its capacity to navigate around the operating space, avoiding obstacles and locating the next location it needs to arrive at. However, due to the high initial costs of production and implementation, digital models of these robots are created first. Digital twined models are created using real-time simulation software, in which multiple aspects are studied regarding the system’s control and modeling to ensure that the implementation of the robot in real-life is as cost-efficient and error-free as can it be.In this paper, a digital model for a three-wheeled omnidirectional robot is created. This robot can potentially be used in various industrial applications as it can move quickly in any direction from any configuration. A simulation program - Simscape a MATLAB-based library - is used for creating a digital twin model for the robot. A hardware prototype is manufactured and a PID controller is used to measure and validate the performance of the proposed digital model.

Evaluation of the Path-Tracking Accuracy of a Three-Wheeled Omnidirectional Mobile Robot Designed as a Personal Assistant.

This paper presents the empirical evaluation of the path-tracking accuracy of a three-wheeled omnidirectional mobile robot that is able to move in any direction while simultaneously changing its orientation. The mobile robot assessed in this paper includes a precise onboard LIDAR for obstacle avoidance, self-location and map creation, path-planning and path-tracking. This mobile robot has been used to develop several assistive services, but the accuracy of its path-tracking system has not been specifically evaluated until now. To this end, this paper describes the kinematics and path-planning procedure implemented in the mobile robot and empirically evaluates the accuracy of its path-tracking system that corrects the trajectory. In this paper, the information gathered by the LIDAR is registered to obtain the ground truth trajectory of the mobile robot in order to estimate the path-tracking accuracy of each experiment conducted. Circular and eight-shaped trajectories were assessed with different translational velocities. In general, the accuracy obtained in circular trajectories is within a short range, but the accuracy obtained in eight-shaped trajectories worsens as the velocity increases. In the case of the mobile robot moving at its nominal translational velocity, 0.3 m/s, the root mean square (RMS) displacement error was 0.032 m for the circular trajectory and 0.039 m for the eight-shaped trajectory; the absolute maximum displacement errors were 0.077 m and 0.088 m, with RMS errors in the angular orientation of 6.27° and 7.76°, respectively. Moreover, the external visual perception generated by these error levels is that the trajectory of the mobile robot is smooth, with a constant velocity and without perceiving trajectory corrections.

Application of Deep Reinforcement Learning for Tracking Control of 3WD Omnidirectional Mobile Robot

Deep reinforcement learning, the fastest growing technique, to solve real-world complex problems by creatinga simple mathematical framework. It includes an agent, action, environment, and a reward. An agent will interactwith the environment, takes an optimal action aiming to maximize the total reward. This paper proposesthe compelling technique of deep deterministic policy gradient for solving the complex continuous actionspace of 3-wheeled omnidirectional mobile robots. Three-wheeled Omnidirectional mobile robots tracking isa difficult task because of the orientation of the wheels which makes it rotate around its own axis rather tofollow the trajectory. A deep deterministic policy gradient (DDPG) algorithm has been designed to train in environmentswith continuous action space to follow the trajectory by training the neural networks defined forthe policy and value function to maximize the reward function defined for the tracking of the trajectory. DDPGagent environment is created in the Reinforcement learning toolbox in MATLAB 2019 while for Actor and criticnetwork design deep neural network designer is used. Results are shown to illustrate the effectiveness of thetechnique with a convergence of error approximately to zero.

Adaptive model predictive control for an omnidirectional mobile robot with friction compensation and incremental input constraints

In this paper, an adaptive model predictive control (MPC) scheme with friction compensation, subject to incremental control input constraints and parameter uncertainties, is proposed for a three-wheeled omnidirectional mobile robot (OMR). The proposed control framework is in a cascaded structure, wherein the outer-loop is kinematic-based control and the inner-loop is designed based on adaptive linear MPC. First, a complex nonlinear dynamic model of the OMR in the world coordinate frame is transformed and partially linearized into a reduced nonlinear model in the moving coordinate system. The nonlinearity of the reduced model only arises from Coulomb friction. Then an estimated system is established for the reduced nonlinear system, with an adaptive update law estimating the system uncertain parameters. To facilitate the linear MPC design, part of the control efforts is derived by feedback compensation of the Coulomb friction forces, resulting in a linear estimated system. The other part is designed by a constrained linear MPC. Feasibility and stability analyses are given for the proposed adaptive MPC scheme. Finally, experimental comparisons with model-based MPC are carried out to verify the effectiveness of the proposed control scheme.

Energy‐optimal transport trajectory planning and online trajectory modification for holonomic robots

AbstractTo maximize energy efficiency, we suggest minimum‐energy trajectory planning and online trajectory modification algorithms for three‐wheeled omni‐directional mobile robots (TOMRs). First, minimum‐energy multisection trajectory planning for various constraints is performed using Pontryagin's minimum principle. Two strategies are established to formulate an efficient minimum‐energy, multisection trajectory generation algorithm: an online trajectory modification and a control algorithm that maintains energy efficiency are investigated using novel heuristic functions. Compared with the conventional trajectory using the trapezoidal velocity profile, the generated transport trajectory can save energy.

The cubic root unscented kalman filter to estimate the position and orientation of mobile robot trajectory

In this paper we introduce a Cubic Root Unscented Kalman Filter (CRUKF) compared to the Unscented Kalman Filter (UKF) for calculating the covariance cubic matrix and covariance matrix within a sensor fusion algorithm to estimate the measurements of an omnidirectional mobile robot trajectory. We study the fusion of the data obtained by the position and orientation with a good precision to localize the robot in an external medium; we apply the techniques of Kalman Filter (KF) to the estimation of the trajectory. We suppose a movement of mobile robot on a plan in two dimensions. The sensor approach is based on the Cubic Root Unscented Kalman Filter (CRUKF) and too on the standard Unscented Kalman Filter (UKF) which are modified to handle measurements from the position and orientation. A real-time implementation is done on a three-wheeled omnidirectional mobile robot, using a dynamic model with trajectories. The algorithm is analyzed and validated with simulations.

Design and FDM/FFF Implementation of a Compact Omnidirectional Wheel for a Mobile Robot and Assessment of ABS and PLA Printing Materials

This paper proposes the design and 3D printing of a compact omnidirectional wheel optimized to create a small series of three-wheeled omnidirectional mobile robots. The omnidirectional wheel proposed is based on the use of free-rotating passive wheels aligned transversally to the center of the main wheel and with a constant separation gap. This paper compares a three inner-passive wheels design based on mass-produced parts and 3D printed elements. The inner passive wheel that better combines weight, cost, and friction is implemented with a metallic ball bearing fitted inside a 3D printed U-grooved ring that holds a soft toric joint. The proposed design has been implemented using acrylonitrile butadiene styrene (ABS) and tough polylactic acid (PLA) as 3D printing materials in order to empirically compare the deformation of the weakest parts of the mechanical design. The conclusion is that the most critical parts of the omnidirectional wheel are less prone to deformation and show better mechanical properties if they are printed horizontally (with the axes that hold the passive wheels oriented parallel to the build surface), with an infill density of 100% and using tough PLA rather than ABS as a 3D printing material.

Dynamic Image-Based Visual Servoing of Monocular Camera Mounted Omnidirectional Mobile Robots Considering Actuators and Target Motion via Fuzzy Integral Sliding Mode Control

In this article, an image-based visual servoing (IBVS) method for monocular camera mounted three-wheeled omnidirectional mobile robots (OMRs) is proposed using a novel fuzzy integral sliding mode control (FISMC) method. Most of the existing studies for IBVS of wheeled mobile robots (WMRs) have focused only on kinematics, even though no consideration for the OMR dynamics, actuators, and target motion can lead to much degraded performance. Accordingly, a camera mounted OMR is first modeled considering the OMR dynamics, actuator dynamics, and disturbance effects of the target object motion. On the basis of the OMR model, a dynamic IBVS method (i.e., IBVS based on kinematics, dynamics, and actuators) is then proposed to replace the kinematic IBVS method (i.e., IBVS based only on kinematics) such that the effects of the OMR dynamics, actuators, and target motion can be accommodated by using the FISMC method. In particular, the proposed FISMC method for the IBVS of OMRs can eliminate the reaching phase to make the states remain on the sliding surface all the time and improve the transient performance significantly when compared with the existing methods. The robust stability of the overall system using the proposed system is demonstrated by Lyapunov stability analysis. Simulation results are also provided to show that where the kinematic IBVS achieves much degraded performance owing to the OMR dynamics and target motion, the proposed FISMC-based dynamic IBVS method compensates for these effects and achieve the satisfactory feature point tracking performance, verifying the effectiveness of the proposed method.

Extended State Observer-Based Sliding Mode Control of an Omnidirectional Mobile Robot With Friction Compensation

This paper presents a reduced-order extended state observer (ESO) based sliding mode control scheme for friction compensation of a three-wheeled omnidirectional mobile robot. Compared with previous works, the proposed control approach is attractive from an implementation point of view. It does not require any explicit friction model, with quite low computation cost. First, a dynamic model with unknown friction forces is given. Then, the controller is designed, consisting of two parts. One part of the control effort is to compensate the friction effects, which are estimated by a reduced-order ESO without using any explicit friction model. The inverse of inertia matrix is also avoided in the proposed reduced-order ESO. The other part of the control effort is designed based on a second-order sliding mode technique known as super-twisting algorithm, in presence of parameter uncertainties. In addition, stability analysis of the designed control system is presented. Extensive experiments are conducted to verify the effectiveness and robustness of the proposed control design in compensating different friction effects.

Energy Modeling and Power Measurement for Three-Wheeled Omnidirectional Mobile Robots for Path Planning

Due to their high mobility, mobile robots (MR) are widely used in intelligent manufacturing. Due to the perfect symmetry of the MR of the three-wheeled moving chassis, it can move quickly in a crowded and complex factory environment. Because it is powered by a lithium battery, in order to improve its energy efficiency, we need to ensure that its power consumption is reduced as much as possible in order to avoid frequent battery replacement. The power consumption of MRs has also become an important research focus for researchers. Therefore, a power consumption modeling of the omnidirectional mobility of the three-wheeled omnidirectional mobile robot (TOMR) is proposed in this paper. When TOMR advances heading at different angles, the speed of each wheel changes dramatically. So, the power consumption of robots will also be greatly changed. In this paper, the energy and power consumption of the robot heading in different directions is analyzed and modeled by formulas. This research can be valuable for path planning and control design.

Passivity-based tracking control of an omnidirectional mobile robot using only one geometrical parameter

This paper presents an output feedback tracking control scheme for a three-wheeled omnidirectional mobile robot, based on passivity property and a modified generalized proportional integral (GPI) observer. The proposed control approach is attractive from an implementation point of view, since only one robot geometrical parameter (i.e., contact radius) is required. Firstly, a nominal dynamic model is given and the passivity property is analyzed. Then the controller is designed based on passivity property and a modified GPI observer. The controller design objective is to preserve the passivity property of the robot system in the closed-loop system, which is conceptually different from the traditional model-based control methodology. Particularly, the designed control system takes full advantage of the robot natural damping. Therefore, only considerably small or non differential feedback is needed. In addition, theoretical analysis is given to show the closed-loop stability behavior. Finally, experiments are conducted to validate the effectiveness of the proposed control system design in both tracking and robustness performance.

Motion Analysis and Control of Three-Wheeled Omnidirectional Mobile Robot

Omnidirectional mobile robots are holonomic vehicles that can perform translational and rotational motions independently and simultaneously. The paper provides a detailed mathematical analysis of the motion of a three-wheeled omnidirectional mobile robot leading to the kinematics of the robot. The motion of the robot can be divided into three types, pure rotation, linear motion and rotation around a point of a nonzero radius. The paper also addresses the problem of trajectory tracking, where the robot has to track the desired trajectory while tracking the desired orientation; to do so; a fuzzy controller has been designed. A comparison made between the proposed controller and another from the literature showed that the fuzzy controller with a minimal number of fuzzy rules (only four rules) is more efficient and more accurate. Furthermore, the paper proposes a simple approach to solve the kinematic saturation problem, namely that the control outputs must be within the range of the admissible control. A simulation platform was carried out using MATLAB to demonstrate the effectiveness of the proposed approach.

Fuzzy Behavior-based Control of Three Wheeled Omnidirectional Mobile Robot

In this paper, a fuzzy behavior-based approach for a three wheeled omnidirectional mobile robot (TWOMR) navigation has been proposed. The robot has to track either static or dynamic target while avoiding either static or dynamic obstacles along its path. A simple controller design is adopted, and to do so, two fuzzy behaviors “Track the Target” and “Avoid Obstacles and Wall Following” are considered based on reduced rule bases (six and five rules respectively). This strategy employs a system of five ultrasonic sensors which provide the necessary information about obstacles in the environment. Simulation platform was designed to demonstrate the effectiveness of the proposed approach.

Minimum-energy cornering trajectory planning with self-rotation for three-wheeled omni-directional mobile robots

A minimum-energy cornering trajectory planning with self-rotation algorithm is investigated for three-wheeled omni-directional mobile robots (TOMRs). First, an generalized minimum-energy point-to-point trajectory planning algorithm is studied, which is obtained using Pontryagin’s minimum principle, a practical cost function as the energy drawn from the batteries to motors, and the accurate TOMR dynamic model including actuator dynamics and the Coriolis force. By analyzing the co-state equation, the minimum-energy rotational velocity trajectory is presented in analytic form. Also a novel algorithm for the minimum-energy translational velocity trajectory is investigated. Second, the minimum-energy cornering trajectory planning algorithm with self-rotation is developed. Simulation results show that the minimum-energy cornering trajectory can save energy up to 15.20%compared with the conventional control using trapezoidal velocity profiles, and up to 3.96 % compared with the loss-minimization control using the armature loss as the cost function. Also a resolved-acceleration controller is implemented to show an actual performance.