Tracked Mobile Robot Research Articles

Trajectory tracking and stabilization of two-wheeled balancing mobile robot with hierarchical and sliding mode control

Trajectory tracking and stabilization of two-wheeled balancing mobile robot with hierarchical and sliding mode control

Distributed Cooperative Control of Heterogeneous Multiagent Systems for Air‐to‐Ground Formation

ABSTRACTThis paper is concerned with a distributed cooperative formation problem for a heterogeneous multiagent system with a car‐like mobile robot, a quadrotor, and an omnidirectional wheeled mobile robot. In the heterogeneous multiagent system, a three‐layer distributed cooperative formation control strategy is constructed to achieve air‐to‐ground formation, the car‐like mobile robot tracks a virtual leader, the quadrotor, and the omnidirectional wheeled mobile robot track the car‐like mobile robot. Two nonlinear leader‐follower controllers based on exponential virtual control laws are designed to maintain formation for the quadrotor and the omnidirectional wheeled mobile robot. A kinematics controller with continuous functions, an improved adaptive sliding mode controller and a suitable back‐stepping controller are introduced in the heterogeneous multiagent system, respectively. Multiagent communication is one of the key steps to accomplish multiagent time synchronization. Experimental results are given to illustrate the applicability of the proposed distributed cooperative control strategy.

Trajectory Tracking of Wheeled Mobile Robot Through System Identification and Control Using Deep Neural Network

Trajectory Tracking of Wheeled Mobile Robot Through System Identification and Control Using Deep Neural Network

Safety-Critical Trajectory Tracking for Mobile Robots with Guaranteed Performance

Safety-Critical Trajectory Tracking for Mobile Robots with Guaranteed Performance

Sliding-mode control for target tracking of omnidirectional mobile robots subject to impulsive deception attacks

This article focuses on the target tracking of omnidirectional mobile robots (OMRs) subject to impulsive deception attacks. The impulsive deception attacks describe the cyber attacks causing instantaneous changes of system states at uncertain moments. To resist such kind of attacks, sliding-mode control (SMC) strategies are designed for the global asymptotic stability of the tracking errors of the OMRs. With the designed sliding-mode controller, the OMRs are capable of tracking the fixed and time-varying target in an experiment platform consisting of OMRs, wireless router and control center, which shows the robustness of the system with respect to impulsive deception attacks and the effectiveness of theoretical results.

Optimal enhanced backstepping method for trajectory tracking control of the wheeled mobile robot

AbstractThis paper proposes a novel control method applied to the trajectory tracking of the wheeled mobile robot. This method can solve the tracking difficulty caused by the non‐holonomic constraint and the under‐actuated properties. First, according to the kinematic and dynamic tracking error models, the desired velocities for trajectory tracking purposes are obtained. Second, the control method, consisting of an enhanced backstepping controller with fewer gains and an optimization algorithm, is designed. The actual trajectory of the mobile robot is exactly converged and kept at the predefined reference trajectory by the operation of this method. Next, this method with globally uniformly asymptotically stability is theoretically analyzed. Finally, simulation comparisons and physical experiments are conducted in different scenarios. The tracking performance is evaluated by three metrics, namely convergence speed, tracking accuracy and robustness, thus verifying the effectiveness of the novel control method.

Research on extreme obstacle–crossing performance and multi–objective optimization of tracked mobile robot

Stability of obstacle–crossing and structural optimization are important issues in the research of tracked mobile robots. In this paper, in order to fully understand the obstacle–surmounting ability of the robot, the relationship between the position of the center of gravity and the posture of the front and rear swing arms is analyzed. Based on the motion mechanism of the robot crossing obstacles, the geometric model and the dynamic model are established for the key states in the obstacle crossing process. Based on these models, a multi-objective optimization problem for the maximum obstacle–crossing height and minimum driving torque is established during the obstacle crossing process of the robot, which must meet geometric, slip, and stability constraints. To effectively handle the optimization problem of tracked mobile robots, an improved non–dominated sorting genetic algorithm with elite strategy version II based on adaptive genetic strategy (NSGA-II-AGS) is proposed in this paper. Some meaningful relationships between the objective function and the design variables are obtained through sensitivity analysis. Finally, the robot's obstacle-crossing ability was verified through virtual simulation and prototype experiments. These excellent performances enable the proposed NSGA-II-AGS to be qualified for dealing with the multi-objective optimization problem.

Dynamic Modeling and Tracking Of 3-Wheels Omni-Directional Mobile Robot with Manual PID Tuning Method

This paper presents the dynamic modelling and tracking control of a holonomic 3-wheel omni-directional mobile robot. A proportional integral derivative (PID) controller is used, and its performance depends on the dynamic model's accuracy. The controller design for the switched non-linear system is based on both a dynamic model and a kinematic design. A proposed dynamic model averages the contact radius of the 3-wheels. The resultant dynamic model, on average, is non-linear and smooth, serving as a potential solution for model-based control design. The closed-loop simulation results clearly illustrate the dynamic characteristics of the 3-wheels omni-directional mobile robot, offering valuable insights into its behaviour for further analysis and optimisation. Comparative simulation results using MATLAB are presented and demonstrate the effectiveness and legitimacy of the control mechanism. Keywords: Holonomic, kinematic, dynamic model, PID controller, non-linear, omni-directional robot

Simultaneous Tracking and Stabilization of Nonholonomic Wheeled Mobile Robots under Constrained Velocity and Torque

Simultaneous Tracking and Stabilization of Nonholonomic Wheeled Mobile Robots under Constrained Velocity and Torque

A robust interpolated model predictive control based on recurrent neural networks for a nonholonomic differential-drive mobile robot with quasi-LPV representation: computational complexity and conservatism

This paper presents an improved Model Predictive Control (MPC) for path tracking of a nonholonomic mobile robot with a differential drive. Nonlinear dynamics and nonholonomic constraints make the optimisation problem of MPC for the robot challenging. Nonlinear dynamics of the robots are expressed by a Linear Parameter Varying (LPV), and a Recurrent Neural Network (RNN) solves the constrained optimisation problem, providing optimal velocities. Moreover, an interpolation-based approach has been introduced to augment the region of attraction. The algorithm ensures stability in the presence of bounded disturbances through the inclusion of free control moves in the control law. The controller efficiency has been evaluated in two scenarios in a hospital setting. The simulation results illustrate that the proposed method performs better than nonlinear MPC and standard LPV-based MPC in terms of computational cost, disturbance rejection, and region of attraction.

MOBILE ROBOT TRACKING SYSTEM BASED ON MACHINE VISION AND LASER RADAR

The proposed solution addresses the issue of insufficient real-time performance and accuracy in mobile robot path tracking by introducing a system that combines machine vision and laser radar. In this study, the Broadcom BCM2711 microcontroller chip is connected to the RS232 communication interface for transmitting information to the ARM embedded processor. Users can access position distance, direction, and other robot-related data through the man-machine interface's LCD display in a Windows operating system environment. By initiating an adaptive position tracking algorithm program identified by the robot within the position tracking unit, mobile position tracking of the robot is achieved. Experimental results demonstrate significant improvements in both real-time performance and accuracy of this mobile robot tracking system.

Correction: Trajectory Tracking of Differential Wheeled Mobile Robots with Input Saturation and Mismatched Centers

Correction: Trajectory Tracking of Differential Wheeled Mobile Robots with Input Saturation and Mismatched Centers

Precise trajectory tracking of mecanum-wheeled omnidirectional mobile robots via a novel fixed-time sliding mode control approach

Precise trajectory tracking of mecanum-wheeled omnidirectional mobile robots via a novel fixed-time sliding mode control approach

Visual Servoing Trajectory Tracking and Depth Identification for Mobile Robots With Velocity Saturation Constraints

Visual Servoing Trajectory Tracking and Depth Identification for Mobile Robots With Velocity Saturation Constraints

Sliding mode observer-based model predictive tracking control for Mecanum-wheeled mobile robot

This paper proposes a novel adaptive variable power sliding mode observer-based model predictive control (AVPSMO-MPC) method for the trajectory tracking of a Mecanum-wheeled mobile robot (MWMR) with external disturbances and model uncertainties. First, in the absence of disturbances and uncertainties, a model predictive controller that considers various physical constraints is designed based on the nominal dynamics model of the MWMR, which can transform the tracking problem into a constrained quadratic programming (QP) problem to solve the optimal control inputs online. Subsequently, to improve the anti-jamming ability of the MWMR, an AVPSMO is designed as a feedforward compensation controller to suppress the effects of external disturbances and model uncertainties during the actual motion of the MWMR, and the stability of the AVPSMO is proved via Lyapunov theory. The proposed AVPSMO-MPC method can achieve precise tracking control while ensuring that the constraints of MWMR are not violated in the presence of disturbances and uncertainties. Finally, comparative simulation cases are presented to demonstrate the effectiveness and robustness of the proposed method.

Trajectory tracking of a wheeled mobile robot based on the predefined‐time sliding mode control scheme

AbstractIn this paper, a double‐loop control method is proposed to improve the trajectory tracking performance of a wheeled mobile robot (WMR) with slippage properties and external disturbances. Considering the strong robustness and the ability to enable the system to converge in a short time, the predefined‐time sliding mode control (PTSMC) strategy is applied to the design of a double‐loop controller. Furthermore, a nonlinear disturbance observer (NDO) is adopted to comply with the feedforward compensation of the external disturbances. In turn, the controller only needs to deal with the internal disturbance of the system under the premise of using the NDO, thereby reducing the burden of the sliding mode controller. Based on Lyapunov methods, the stability of the double‐loop controller and the NDO is analyzed. Finally, the feasibility of the double‐loop control strategy is proven by simulations of the WMR operating along circular, sin‐shaped, and eight‐shaped roads.

Consensus-Based Information Filtering in Distributed LiDAR Sensor Network for Tracking Mobile Robots.

A distributed state observer is designed for state estimation and tracking of mobile robots amidst dynamic environments and occlusions within distributed LiDAR sensor networks. The proposed novel framework enhances three-dimensional bounding box detection and tracking utilizing a consensus-based information filter and a region of interest for state estimation of mobile robots. The framework enables the identification of the input to the dynamic process using remote sensing, enhancing the state prediction accuracy for low-visibility and occlusion scenarios in dynamic scenes. Experimental evaluations in indoor settings confirm the effectiveness of the framework in terms of accuracy and computational efficiency. These results highlight the benefit of integrating stationary LiDAR sensors' state estimates into a switching consensus information filter to enhance the reliability of tracking and to reduce estimation error in the sense of mean square and covariance.

Formation and Trajectory Tracking of Mobile Robots with Uncertainties and Disturbances Using an Adaptive Immune Fuzzy Quasi-Sliding Mode Control

Formation and Trajectory Tracking of Mobile Robots with Uncertainties and Disturbances Using an Adaptive Immune Fuzzy Quasi-Sliding Mode Control

Trajectory tracking of mobile robots using hedge-agebras-based controllers

Trajectory tracking of mobile robots using hedge-agebras-based controllers

Trajectory tracking for non-holonomic mobile robots: A comparison of sliding mode control approaches

This paper implements and compares the performance of three controllers based on Sliding Mode Control (SMC) applied to the motion control of mobile robots. The controllers include a standard SMC controller and two variations, namely Dynamic Sliding Mode Control (D-SMC) and Dual Sliding Mode Control (DM-SMC). The three controllers differ from conventional SMC approaches since they are designed based on a generic reduced-order empirical model that can represent any system that exhibits behavior akin to a First-Order Plus Delay Time (FOPDT) system. In this study, the comparison of controllers focuses on the Trajectory Tracking Problem (TTP) of a Nonholonomic Mobile Robot (NMR). Performance indices are employed to quantify the controllers' results across three trajectory types. Simulation results evidence that if a smooth curvature trajectory is tracked, the best performance (in terms of minimizing trajectory tracking error and controller effort) can be obtained by using a DM-SMC. On the other hand, if there are discontinuities in the curvature, the results suggest that a better alternative is the D-SMC since it compensates for abrupt changes as in the case of tracking a square trajectory. Overall, the findings from this work demonstrated that the use of simplified empirical models to design SMC-based motion controllers can be successfully applied to solve the TTP of NMR.