Nonholonomic Wheeled Mobile Robots Research Articles

Formation control for multiple nonholonomic wheeled mobile robots based on integrated sliding mode controller and force function

In this paper, we present a novel method to achieve collision-free formation control for multiple nonholonomic wheeled mobile robots. By utilizing the leader–follower strategy, an integrated controller that combines a sliding mode controller for formation control and a force function for obstacle avoidance is proposed. To address the common chattering issue associated with sliding mode control, a novel depletion model is developed, which constrains the controller input to vary smoothly within a small range and effectively eliminates chattering. Additionally, a dynamic-gain structure is introduced to reconcile the conflicting demands of formation control and obstacle avoidance, providing enhanced coordination between the two tasks. Simulation and experiments’ results are provided to illustrate the effectiveness of the proposed method.

Research on trajectory tracking of wheeled mobile robots using fuzzy PID based on TD3

Abstract This study addresses the issues and limitations of trajectory tracking for Non-holonomic wheeled mobile robot (NWMR) under traditional PID control, including low accuracy, high response delay, poor robustness, and stability concerns. We propose a strategy that combines the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm with fuzzy PID control to optimize PID parameter tuning for more precise robot trajectory tracking. Fuzzy logic is introduced to adjust the PID controller parameters, making them more adaptive and robust. The bidirectional long short-term memory (BiLSTM) network enhances the time series processing capability of the Actor-Critic network, improving the system’s state representation and prediction abilities. A curiosity-driven exploration method is employed to increase policy diversity and avoid premature convergence. Simulation experiments using the ROS Noetic and Gazebo platforms demonstrate that this method significantly outperforms traditional PID and TD3 algorithms in terms of trajectory alignment, training time, accuracy, and stability.

FF-RRT*: A Sampling-Based Planner for Multirobot Global Formation Path Planning

Abstract This article presents a collision-free global path planning approach for multirobot systems called flexible formation—rapidly exploring randomized trees* (FF-RRT*). The algorithm is based on RRT* and provides a flexible and efficient representation of the formation geometry independent of the number of robots. It is designed to generate optimal paths for multirobot systems in a five-dimensional configuration space comprising the formation centroid, orientation, and scaling. An affine transformation is used to convert the path in the configuration space to the workspace of the robots. The proposed method employs a new distance function that eliminates the need for tuning weights and a sampling scheme for scaling factors to avoid inter-robot collisions. FF-RRT* is experimentally demonstrated using nonholonomic wheeled mobile robots and is effective in planning the collective motion of the robots. Robots could collectively reach goals by squeezing through narrow gaps and splitting and merging around large obstacles.

Motion/force coordinated trajectory tracking control of nonholonomic wheeled mobile robot via LMPC-AISMC strategy

Nonholonomic constrained wheeled mobile robot (WMR) trajectory tracking requires the enhancement of the ground adaptation capability of the WMR while ensuring its attitude tracking accuracy, a novel dual closed-loop control structure is developed to implement this motion/force coordinated control objective in this paper. Firstly, the outer-loop motion controller is presented using Laguerre functions modified model predictive control (LMPC). Optimised solution condition is introduced to reduce the number of LMPC solutions. Secondly, an inner-loop force controller based on adaptive integral sliding mode control (AISMC) is constructed to ensure the desired velocity tracking and output driving torques by combining second-order nonlinear extended state observer (ESO) with the estimation of dynamic uncertainties and external disturbances during WMR travelling process. Then, Lyapunov stability theory is utilised to guarantee the consistent final boundedness of the designed controller. Finally, the system is numerically simulated and practically verified. The results show that the double-closed-loop control strategy devised in this paper has better control performance in terms of complex trajectory tracking accuracy, system resistance to strong interference and computational timeliness, and is able to realise effective coordinated control of WMR motion/force.

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

Observer-Based Trajectory Tracking Control of Nonholonomic Wheeled Mobile Robots

Observer-Based Trajectory Tracking Control of Nonholonomic Wheeled Mobile Robots

Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots: A Barrier Function Sliding Mode Approach

Adaptive Trajectory Tracking Control for Nonholonomic Wheeled Mobile Robots: A Barrier Function Sliding Mode Approach

Model predictive control for non-holonomic robots with disturbances: A quasi-differential type event-driven method

For non-holonomic wheeled mobile robots with coupled constraints and bounded disturbances, a novel event-driven model predictive control (EMPC) strategy is designed in this paper. Firstly, to alleviate the computational and data transmission burden of the system, an EMPC algorithm considering the quasi-differential information of continuous state discrepancies is proposed, rather than only considering the system state at a single moment. Secondly, to accelerate the convergence speed of the system state, an exponential robust constraint is introduced when designing the optimization problem. Furthermore, the parameter conditions that ensure the feasibility and system stability are theoretically provided. In the end, simulation and comparison are provided to demonstrate the effectiveness of this algorithm.

A finite-time path-tracking control algorithm for nonholonomic mobile robots with unknown dynamics and subject to wheel slippage/skid disturbances

Path planning and tracking control are two performance-critical tasks for wheeled mobile robots, particularly when nonholonomic constraints are imposed on robots in dynamically uncertain conditions. Accomplishing certain performance and safety considerations related to path-tracking, such as global stability, transient performance, and smooth finite-time convergence, becomes more difficult for nonholonomic robots. This paper is concerned with proposing a new adaptive robust finite-time tracking control approach for a large class of differential drive autonomous nonholonomic wheeled mobile robots (NWMRs) that are subject to structured uncertainties and extraneous disturbances with fully unknown dynamics. For this purpose, nonlinear kinodynamics of a type of rear-wheel drive NWMRs are developed by incorporating the skid/slippage constituents of the wheel motion. Then, a path-tracking controller is proposed using a continuous finite-time adaptive integral sliding mode control coupled with an integral backstepping approach (FTAISM-IBC). For the adaptive controller design, the entire nonlinear dynamics of the robot, including nonlinear vector functions and control gain functions, together with extraneous disturbances, are estimated by leveraging the universal approximation capabilities of radial basis neural networks (RBFNNs). The finite-time stability proof is presented by utilizing the Lyapunov stability theorem. Furthermore, the adaptive gains are derived to ensure the finite-time stability of the system subject to unknown functions, parametric variations, and unknown but bounded disturbances. Finally, the effectiveness of the proposed controller is evaluated through simulations in terms of several key performance indicators against several reported studies.

Adaptive fuzzy sliding mode control of uncertain nonholonomic wheeled mobile robot with external disturbance and actuator saturation

This paper developed a modified barrier function-based adaptive sliding mode control (MBFASMC) method to improve the tracking precision and robustness performance of the nonholonomic wheeled mobile robot (NWMR), which is subject to actuator saturation and external disturbance. Owing to the modified positive semi-definite barrier function (MPSDBF), the requirement for disturbance bound and the overestimation of control gain are eliminated. The nonsingular terminal sliding manifold and MPSDBF-based adaptive mechanism can guarantee that the sliding variables and the posture errors of NWMR converge to precisely predefined ultimate bounds in a finite time. In order to compensate for the adverse effect of input saturation, an auxiliary dynamics is proposed based on saturation error and used to construct the MBFASMC. Compared to the recent anti-saturation control methods, the demand for saturation level is released in the proposed control method. Moreover, a modified barrier function-based adaptive fuzzy sliding mode control (MBFAFSMC) is provided to relieve the control chattering problem. By Lyapunov analysis, it is validated that the proposed methods can ensure the pre-specified and finite-time convergence performance of the uncertain NWMR. The MBFASMC and MBFAFSMC are also applied to an actual NWMR experimental platform with artificial disturbances to verify the effectiveness of the proposed methods.

Research on Some Control Algorithms to Compensate for the Negative Effects of Model Uncertainty Parameters, External Interference, and Wheeled Slip for Mobile Robot

In this article, the research team systematically developed a method to model the kinematics and dynamics of a 3-wheeled robot subjected to external disturbances and sideways wheel sliding. These models will be used to design control laws that compensate for wheel slippage, model uncertainties, and external disturbances. These control algorithms were developed based on dynamic surface control (DSC). An adaptive trajectory tracking DSC algorithm using a fuzzy logic system (AFDSC) and a radial neural network (RBFNN) with a fuzzy logic system were used to overcome the disadvantages of DSC and expand the application domain for non-holonomic wheeled mobile robots with lateral slip (WMR). However, this adaptive fuzzy neural network dynamic surface control (AFNNDSC) adaptive controller ensures the closed system is stable, follows the preset trajectory in the presence of wheel slippage model uncertainty, and is affected by significant amplitude disturbances. The stability and convergence of the closed-loop system are guaranteed based on the Lyapunov analysis. The AFNNDSC adaptive controller is evaluated by simulation on the Matlab/simulink software R2022b and in a steady state. The maximum position error on the right wheel and left wheel is 0.000572 (m) and 0.000523 (m), and the angular velocity tracking error in the right and left wheels of the control method is 0.000394 (rad/s). The experimental results show the theoretical analysis’ correctness, the proposed controller’s effectiveness, and the possibility of practical applications. Orbits are set as two periodic functions of period T as follows.

Adaptive terminal sliding mode control of a non-holonomic wheeled mobile robot

Adaptive terminal sliding mode control of a non-holonomic wheeled mobile robot

Adaptive terminal sliding mode control of a non-holonomic wheeled mobile robot

Adaptive terminal sliding mode control of a non-holonomic wheeled mobile robot

Retracted: Distributed Consensus Algorithm for Nonholonomic Wheeled Mobile Robot

Retracted: Distributed Consensus Algorithm for Nonholonomic Wheeled Mobile Robot

A novel saturated PID‐type observer‐based controller for wheeled mobile robots with a guaranteed performance considering path curvature

AbstractThis article proposes a novel saturated PID‐type formation controller for a class of nonholonomic wheeled mobile robots (WMRs) of type (m, s) with mobility m and steerability s. Since the path curvature causes a severe deviation of the followers from the leaders' trajectory in the corners, a new definition of output equations is suggested to construct the coordinates of a virtual reference point in the front of each follower based on the concept of the extended look‐ahead control that utilizes a corrective angle to compensate the trajectory curvature efficiently. A nonlinear transformation and the robot's kinematic and dynamic equations are heuristically combined to develop a novel second‐order Euler–Lagrange formulation of unconstrained errors from constrained errors. Then, a novel saturated PID‐type controller is proposed for WMRs to build a desirable formation with a prescribed performance. An innovative nonlinear observer is presented to estimate followers' velocities. An efficient mixture of a radial basis function neural network (RBFNN) and an adaptive mechanism is proposed to compensate for model uncertainties, external disturbances, and network approximation errors. Lyapunov's direct method verifies semi‐global uniform ultimate boundedness stability by estimating a gain‐dependent region of attraction. Numerical simulations finally show the efficiency of the proposed controller.

Formation control of nonholonomic wheeled mobile robots using adaptive distributed fractional order fast terminal sliding mode control

Formation control of nonholonomic wheeled mobile robots using adaptive distributed fractional order fast terminal sliding mode control

Trajectory tracking control of nonholonomic wheeled mobile robots using only measurements for position and velocity

This paper studies the trajectory tracking control of nonholonomic wheeled mobile robots, and only measurements for Cartesian position and velocity are used. A full-order observer is proposed to estimate the unmeasurable attitude and filter the position signal. Its effectiveness relies on the persistent excitation (PE) condition of non-zero linear velocity. Using the observer states, we design a local tracking controller that guarantees: (a) the linear velocity input is positive, and (b) the position tracking error is convergent to zero locally asymptotically. Experiments performed on a robot built in-house illustrate the control algorithm.

End-to-End Autonomous Navigation Based on Deep Reinforcement Learning with a Survival Penalty Function.

An end-to-end approach to autonomous navigation that is based on deep reinforcement learning (DRL) with a survival penalty function is proposed in this paper. Two actor-critic (AC) frameworks, namely, deep deterministic policy gradient (DDPG) and twin-delayed DDPG (TD3), are employed to enable a nonholonomic wheeled mobile robot (WMR) to perform navigation in dynamic environments containing obstacles and for which no maps are available. A comprehensive reward based on the survival penalty function is introduced; this approach effectively solves the sparse reward problem and enables the WMR to move toward its target. Consecutive episodes are connected to increase the cumulative penalty for scenarios involving obstacles; this method prevents training failure and enables the WMR to plan a collision-free path. Simulations are conducted for four scenarios-movement in an obstacle-free space, in a parking lot, at an intersection without and with a central obstacle, and in a multiple obstacle space-to demonstrate the efficiency and operational safety of our method. For the same navigation environment, compared with the DDPG algorithm, the TD3 algorithm exhibits faster numerical convergence and higher stability in the training phase, as well as a higher task execution success rate in the evaluation phase.

Design and implementation of resource‐aware robust event‐based integral sliding mode controller for a networked wheeled mobile robot

AbstractThis work discusses the design and implementation of a robust control strategy based on integral sliding mode (ISM) for tracking a reference trajectory by a nonholonomic wheeled mobile robot (WMR). A state feedback control law using dynamic feedback linearization is adopted to design the controller for the unperturbed dynamics of the WMR. To nullify the effects of perturbations in the WMR and to retain the performance of the nominal controller, the ISM control scheme is introduced, which uses discontinuous control to guarantee the robustness of the closed‐loop system. To relax the frequent use of the communication network due to the continuous exchange of the sensor measurements, the control law is redesigned using event‐based sampled data information. The control signal is updated in an aperiodic manner by designing a novel triggering rule where the triggering occurs only when either of the two sampling errors violates a predefined threshold condition. This design approach gives a balanced solution for a networked WMR regarding network usage and control performance. Finally, a simulation study with comparative analysis and hardware‐in‐loop testing of the proposed controller is performed on a mobile robot system to establish the feasibility of the theoretical results.

Fixed-time integral sliding mode tracking control of a wheeled mobile robot

This paper presents a fixed-time integral sliding mode control scheme for a nonholonomic wheeled mobile robot (WMR). To achieve the trajectory tracking mission, the dynamic model of a WMR is first transformed into a second-order attitude subsystem and a third-order position subsystem. Two novel continuous fixed-time disturbance observers are proposed to estimate the external disturbances of the two subsystems, respectively. Then, trajectory tracking controllers are designed for two subsystems by utilizing the reconstructed information obtained from the disturbance observers. Additionally, an auxiliary variable that incorporates the Gaussian error function is introduced to address the chattering problem of the control system. Finally, the proposed control scheme is validated by a wheeled mobile robotic experimental platform.