Control Of Nonholonomic Mobile Robot Research Articles

Fixed-Time Event-Triggered Control of Nonholonomic Mobile Robots with Uncertain Dynamics and Preassigned Transient Performance

In this paper, a novel adaptive control scheme is proposed for the path-following problem of a nonholonomic mobile robot with uncertain dynamics based on barrier functions. To optimize communication resources, we integrate an event-triggered mechanism that avoids Zeno behavior and ensures that the tracking error of the closed-loop system converges to a small neighborhood around zero within a fixed time, while consistently satisfying predefined transient performance requirements. Extensive simulation studies demonstrate the effectiveness of the proposed approach and validate the theoretical results.

Decentralized, norm-free, and adaptive event-triggered distributed control of nonholonomic mobile robots

The overarching contribution of this paper is a novel event-triggered distributed control architecture for multiagent systems that are composed of a team of nonholonomic mobile robots. Specifically, the robot dynamics are first feedback linearised to equivalently represent each robot with double integrator dynamics and the event-triggering law is then presented. This law is characterised by being decentralised (depending only on own signals of a robot), norm-free (independent of distances for reducing robot-to-robot data transmissions), and adaptive (estimating signals without using global information). Moreover, its system-theo- retical analysis is provided, which holds for both the sampled data exchange method and the solution-predictor curve-based data exchange method. In contrast to the well-studied sampled data exchange, the solution-predictor curve method further reduces robot-to-robot data transmissions by making each agent to store a generic form of this curve and exchange its parameters when an event occurs for approximating the solution trajectory of each robot. Finally, an illustrative numerical example is included to demonstrate the overall architecture.

Switched Model Predictive Control for Nonholonomic Mobile Robots Under Adaptive Dwell Time.

In this article, switched model predictive control (MPC) is proposed for nonholonomic mobile robots with adaptive dwell time and a dual-terminal set. The dual-terminal set is used to reduce on-line complexity of the switched MPC for the nonholonomic mobile robots with multiple constraints. By a switched signal with the adaptive dwell time, cost functions are switched to improve control performance under multiple constraints. The switched MPC with feasibility and stability can adjust a tradeoff between control performance and computational complexity for the closed-loop system. Simulation results are given to illustrate superiority of the switched MPC for nonholonomic mobile robots.

Fixed-Time Adaptive Event-Triggered Guaranteed Performance Tracking Control of Nonholonomic Mobile Robots under Asymmetric State Constraints

A fixed-time adaptive guaranteed performance tracking control is investigated for a category of nonholonomic mobile robots (NMRs) under asymmetric state constraints. For the sake of favorable transient and steady-state properties of the system, a prescribed performance function (PPF) is introduced and a transform function is further constructed. Based on the backstepping technique, an asymmetric barrier Lyapunov function is formulated to ensure the tracking errors converge within a human-specified time. On the foundation of this, the occupation of communication channel is effectively reduced by assigning an event-triggered mechanism (ETM) with relative threshold to the process of controller design. By utilizing the proposed control strategy, the NMR is capable of implementing the enemy dislodging mission while the enemy can always be caught by the NMR and the collision would never be presented. Finally, two simulation experiments are given to verify the effectiveness of the proposed scheme.

Autonomous Target Docking With Obstacle Avoidance and Final Velocity Control for Non-Holonomic Mobile Robots

Autonomous Target Docking With Obstacle Avoidance and Final Velocity Control for Non-Holonomic Mobile Robots

Global Consensus-Based Formation Control of Nonholonomic Mobile Robots With Time-Varying Delays and Without Velocity Measurements

We propose a solution to the full consensus-based formation problem for torque-controlled nonholonomic mobile robots under time-varying communication delays and without velocity measurements. Under the assumptions of static and undirected communication topologies, and smooth and bounded delays, we propose a distributed smooth, time-varying control law which achieves the goal of acquiring a global formation pattern in a common consensus point for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">both</i> position and orientation. The controller is a combination of a simple Proportional-Plus-Damping scheme and a simple globally exponentially convergent velocity observer. Consensus is reached independently of all initial conditions. Realistic simulations in the Gazebo-ROS environment illustrate the effectiveness of the proposed algorithm and the robustness with respect to measurement noise, non-smooth delays and uncertain dynamics.

Distributed Prescribed Performance Formation Control for Nonholonomic Mobile Robots Under Noisy Communication

Distributed Prescribed Performance Formation Control for Nonholonomic Mobile Robots Under Noisy Communication

Decentralized Circular Formation Control of Nonholonomic Mobile Robots Under a Directed Sensor Graph

This paper investigates the circular formation control problem of multiple unicycle-type mobile robots under a directed sensor graph. The topology of the sensor graph among all robots is described by a directed graph containing a spanning tree, and the node denoting the center is only required to be globally reachable in the sensor graph. A dynamic control law is developed such that the multi-robot systems with speed constraint are able to globally converge to a circular formation prescribed by a stationary center, a radius, and a spacing configuration. Remarkably, the proposed control law does not rely on any communication, and only requires each robot to use local measurements with respect to its neighbors based on its local coordinate frame, which makes it feasible to implement this control law in a decentralized manner. The global asymptotic stability of the closed-loop multi-robot systems is established by small gain theorem of which the small-gain condition is guaranteed by a low gain parameter in the designed observer.

Formation Control of Non-Holonomic Mobile Robots: Predictive Data-Driven Fuzzy Compensator

A key research topic in the field of robotics is the formation control of a group of robots in trajectory tracking problems. Using organized robots has many advantages over using them individually, such as efficient use of resources, increased reliability due to cooperation, and better resistance against defects. To achieve this, a controller is proposed that steers the leader robot and subsequent follower robots asymptotically to a reference trajectory. The basic controller is feedback linearization. To ensure stability against perturbations, a compensator based on type-3 fuzzy logic systems (T3-FLSs) and a data-driven control strategy is designed. The approach involves employing a finite number of open-loop data and using the model-based predictive controller (MPC) approach to acquire sufficient criteria for stability. An infinite-horizon function is minimized online, which allows the data-based control policy to be considered the optimal control method. The gains of the constrained data-based control signal are computed at each time step to enhance accuracy. Applying the data-based state feedback controller to the system yields positive and stable state trajectories with appropriate transient responses. The suggested data-driven compensator is guaranteed to handle constraints. A practical example is simulated to evaluate the proposed strategy.

Cooperative Control of Multirobot Systems Subject to Control Gain Uncertainty

This article addresses the problem of cooperative control of double-integrator type multirobot systems. Different from some conventional results with the control gain explicitly known, the control gain in this article is subject to uncertainty. Three different collective behaviors are explored, i.e., leaderless consensus, leader-following consensus, and formation control. For leaderless consensus, a sliding variable is constructed, based on which a novel continuous controller is designed such that the sliding surface is reached in finite-time and thus the state agreement of all agents is realized. For leader-following consensus, two different cases are investigated, i.e., the leader with constant velocity and with time-varying velocity. In both cases, sliding-mode based controllers are developed and corresponding stability conditions are established to ensure that the leader state is tracked by all followers. Finally, the theoretical results are applied to achieve formation control of nonholonomic mobile robots and corresponding experimental studies are conducted to demonstrate the effectiveness of the proposed controllers.

Leader-Following Formation Tracking Control of Nonholonomic Mobile Robots Considering Collision Avoidance: A System Transformation Approach

In this paper, the obstacle avoidance problem-based leader–following formation tracking of nonholonomic wheeled mobile robots with unknown parameters of desired trajectory is investigated. First, the under-actuated system is transformed into a fully-actuated system by obtaining an auxiliary control variable using the transverse function. Second, by introducing a potential function for each obstacle, the influence of obstacles is considered in trajectory tracking, and the effect of the potential field on mobile robots is taken into account in the system tracking error. Third, the adaptive laws are designed to estimate the unknown parameters of the desired trajectory. Fourth, the results show that the formation error with respect to the actual position and orientation can be arbitrarily small by selecting appropriate design parameters. Finally, simulation examples are used to demonstrate that the proposed control scheme is effective.

Formation control of nonholonomic mobile robots with inaccurate global positions and velocities

AbstractIn this article, leader‐following formation control is investigated for nonholonomic mobile robots with inaccurate measurements of global positions and velocities. In many existing results, the leader robot's velocities are assumed to be precisely measured and transmitted to follower robots, and unmodeled parts of the kinematic model caused by inaccurate global position are often ignored. First, an error‐based extended state observer (EBESO) for each robot is designed to counteract influence of the inaccurate global positions and velocities in real time. Then, an EBESO‐based formation controller without the leader robot's velocities is proposed to guarantee the accurate formation tracking performances. Furthermore, both convergence of the EBESO and stability analysis of the closed‐loop error system are provided, respectively. The superiority of the proposed method is verified and illustrated by experiments.

Path-Guided Finite-Time Formation Control of Nonholonomic Mobile Robots Based on an Extended State Observer

In this paper, we study the finite-time formation control problem of uncertain nonholonomic mobile robots following a parameterized path. A path-guided formation control scheme based on an extended state observer is proposed. To compensate for unmeasured velocities and disturbances simultaneously, a third-order fast finite-time extended state observer (FFTESO) is proposed. Then, a distributed formation control solution is developed to achieve the kinematic and dynamic system coordination control of the nonholonomic mobile robots. For the kinematic system control, a path-parameter-updating law is developed for a virtual leader, and the desired linear velocity and heading angle are developed for the mobile robots. For the kinetic control, an anti-disturbance control protocol is designed based on the estimated signals. The salient features of the proposed algorithms lie in that the estimations of disturbances and unmeasured velocities are achieved against the system’s nonholonomic constraints, and the path following the control and cooperative control is synthesized together for path-guided formation, which reduces the complexity of the controller design. Finally, simulation studies are conducted to demonstrate the effectiveness of the proposed algorithm.

A Smooth Time–Varying PID Controller for Nonholonomic Mobile Robots Subject to Matched Disturbances

A Smooth Time–Varying PID Controller for Nonholonomic Mobile Robots Subject to Matched Disturbances

Robust PID consensus-based formation control of nonholonomic mobile robots affected by disturbances

In this work, we report a novel controller to solve (globally) the position and orientation consensus-based formation problem of multiple nonholonomic vehicles modelled as differential drive robots affected by external disturbances. The controller has the structure of a simple to implement Proportional Integral Derivative (PID) scheme. In order to satisfy the well-known Brocket stabilisation theorem for nonholonomic systems, we also incorporate a time-varying persistency of excitation term in the angular velocity dynamics. Our proposal reports the first solution to the robust formation problem using a smooth time-varying controller. Simulations are shown to evidence the theoretical findings of this work.

Leader-following consensus control of multiple nonholomomic mobile robots: An iterative learning adaptive control scheme

In this paper, the distributed iterative learning control for nonholonomic mobile robots with a time-varying reference is investigated, in which the mobile robots are with parametric uncertainties and are not fully actuated. Besides, the control gains of mobile robots are unknown. The leader is with a time-varying reference trajectory , and there is no need to assume that the time-varying reference is linearly parameterized by a set of known functions. A distributed control scheme is designed for each mobile robot based on a set of local compensatory filters designed by its neighborhood information. Stability analysis is established through a set of composite energy function. The uniform convergence of the consensus errors can be guaranteed. An example is given to show that our designed control law is effective.

Semantic segmentation based stereo visual servoing of nonholonomic mobile robot in intelligent manufacturing environment

In the interest of developing an intelligent manufacturing environment with an agile, efficient, and optimally utilized transportation system, mobile robots need to achieve a certain level of autonomy as they play an important role in carrying out transportation tasks. Bearing this in mind, in the paper we propose a novel stereo visual servoing method for nonholonomic mobile robot control based on semantic segmentation. Semantic segmentation provides a rich body of information required for an adequate decision-making process in a clustered, dynamic, and ever-changing manufacturing environment. The innovative idea behind the new visual servoing system is to utilize semantic information of the scene for visual servoing, as well as for other mobile robot tasks, such as obstacle avoidance, scene understanding, and simultaneous localization and mapping. Semantic segmentation is carried out by exploiting fully convolutional neural networks. The new visual servoing algorithm utilizes an intensity-based image registration procedure, which results in the image transformation matrix. The transformation matrix encompasses the relations of images taken at the current and desired pose, and that information is directly used for visual servoing. The developed algorithm is deployed on our own developed wheeled differential drive mobile robot RAICO (Robot with Artificial Intelligence based COgnition). The experimental evaluation is carried out in the 3D simulation environment and in the laboratory model of the real manufacturing environment. The experimental results show that the accuracy of the proposed approach is improved when compared to the state-of-the-art approaches while being robust to the partial occlusions of the scene and illumination changes.

The Analysis of Trajectory Control of Non-holonomic Mobile Robots Based on Internet of Things Target Image Enhancement Technology and Backpropagation Neural Network.

The trajectory tracking and control of incomplete mobile robots are explored to improve the accuracy of the trajectory tracking of the robot controller. First, the mathematical kinematics model of the non-holonomic mobile robot is studied. Then, the improved Backpropagation Neural Network (BPNN) is applied to the robot controller. On this basis, a mobile robot trajectory tracking controller combining the fuzzy algorithm and the neural network is designed to control the linear velocity and angular velocity of the mobile robot. Finally, the robot target image can be analyzed effectively based on the Internet of Things (IoT) image enhancement technology. In the MATLAB environment, the performances of traditional BPNN and improved BPNN in mobile robots' trajectory tracking are compared. The tracking accuracy before and after the improvement shows no apparent differences; however, the training speed of improved BPNN is significantly accelerated. The fuzzy-BPNN controller presents significant improvements in tracking speed and tracking accuracy compared with the improved BPNN. The trajectory tracking controller of the mobile robot is designed and improved based on the fuzzy BPNN. The designed controller combining the fuzzy algorithm and the improved BPNN can provide higher accuracy and tracking efficiency for the trajectory tracking and control of the non-holonomic mobile robots.

Motion planning and control of nonholonomic mobile robot using flatness and fuzzy logic concepts

This paper presents a fuzzy-flatness technique for the efficient manipulation of mobile robots with nonholonomic constraints. A decoupled “path trajectory” planning approach is firstly defined to ensure the generation of reference trajectories that respect the nonholonomic constraints. An auto-tuned endogenous feedback control law is then designed to ensure good tracking of the desired tasks despite uncertainties. The controller gains are adjusted online by using a suitable fuzzy controller. Based on the developed algorithm and the laboratory test prototype Pioneer-3dx, numerical tests were carried out to evaluate the performances of the proposed approach.

A Comparison of Different Approaches for Formation Control of Nonholonomic Mobile Robots regarding Object Transport

Abstract Controlling the formation of several mobile robots allows for the connection of these robots to a large virtual unit. This enables a group of mobile robots to carry out tasks that a single robot could not perform. For this purpose, the use of nonholonomic mobile robots is especially useful, as they often have a higher payload and are suitable for a wider range of terrains. However, most research in the area of formation control is focused on holonomic robots, since their superior mobility allows for better control and allows for the research on more sophisticated control techniques. The remaining articles explicitly dealing with nonholonomic robots often do cover common controllers, but do not include realistic simulations or comparison of different controls on the same trajectory. Therefore, in this paper, we present a comparative analysis of two frequently used control approaches. We compare the behavior of a l-ψ-controller and a Cartesian reference-based controller with different types of reference value generation and pose determination. The evaluation of all resulting control schemes is based on the task of collaborative object transport. To do so, we selected performance criteria geared towards applicability in real processes. In addition, we used an error model, which takes into account the noise and accuracy of all sensors (IMU and encoder) as well as the drift in odometry caused by the slip of the robot’s wheels. The comparison includes a series of simulations using two trajectories with a changing number of robots and different formation geometries. In the simulations we got slightly better results for the Cartesian control law.