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

The trajectory tracking control performance of nonholonomic wheeled mobile robots(NWMRs)is subject to nonholonomic constraints,system uncertainties,and external disturbances.This paper proposes a barrier function-based adaptive sliding mode control(BFASMC)method to provide high-precision,fast-response performance and robustness for NWMRs.Compared with the conventional adaptive sliding mode control,the proposed control strategy can guarantee that the sliding mode variables converge to a predefined neighborhood of origin with a predefined reaching time independent of the prior knowledge of the uncertainties and disturbances bounds.Another advantage of the proposed algorithm is that the control gains can be adaptively adjusted to follow the disturbances amplitudes thanks to the barrier function.The benefit is that the overestimation of control gain can be eliminated,resulting in chattering reduction.Moreover,a modified barrier function-like control gain is employed to prevent the input saturation problem due to the physical limit of the actuator.The stability analysis and comparative experiments demonstrate that the proposed BFASMC can ensure the prespecified convergence performance of the NWMR system output variables and strong robustness against uncertainties/disturbances.

A finite-time fuzzy adaptive output-feedback fault-tolerant control for underactuated wheeled mobile robots systems

This paper investigates the adaptive fuzzy finite-time output-feedback fault-tolerant control (FTC) problemfor a class of nonlinear underactuated wheeled mobile robots (UWMRs) system with intermittent actuatorfaults. The UWMR system includes unknown nonlinear dynamics and immeasurable states. Fuzzy logic systems(FLSs) are utilized to work out immeasurable functions. Furthermore, with the support of the backsteppingcontrol technique and adaptive fuzzy state observer, a fuzzy adaptive finite-time output-feedback FTC scheme isdeveloped under the intermittent actuator faults. It is testifying the scheme can ensure the controlled nonlinearUWMRs is stable and the estimation errors are convergent. Finally, the comparison results and simulationvalidate the effectiveness of the proposed fuzzy adaptive finite-time FTC approach.

NuBot:A Magnetic Adhesion Robot with Passive Suspension to Inspect the Steel Lining

The steel lining of huge facilities is a significant structure,which experiences extreme environments and needs to be inspected periodically after manufacture.However,due to the complexity(crisscross welds,curved surface,etc.)of their inside environments,high demands for stable adhesion and curvature adaptability are put forward.This paper presents a novel wheeled magnetic adhesion robot with passive suspension applied in nuclear power containment called NuBot,and mainly focuses on the following aspects:(1)proposing the wheeled locomotion suspension to adapt the robot to the uneven surface;(2)implementing the parameter optimization of NuBot.A comprehensive optimization model is established,and global optimal dimensions are properly chosen from performance atlases;(3)determining the normalization factor and actual dimensional parameters by constraints of the steel lining environment;(4)structure design of the overall robot and the magnetic wheels are completed.Experiments show that the robot can achieve precise locomotion on both strong and weak magnetic walls with various inclination angles,and can stably cross the 5 mm weld seam.Besides,its maximum payload capacity reaches 3.6 kg.Results show that the NuBot designed by the proposed systematic method has good comprehensive capabilities of surface-adaptability,adhesion stability,and payload.Besides,the robot can be applied in more ferromagnetic environments and the design method offers guidance for similar wheeled robots with passive suspension.

Analytical modeling and multi-objective optimization(MOO) of slippage for wheeled mobile robot(WMR) in rough terrain

Good understanding of relationship between parameters of vehicle, terrain and interaction at the interface is required to develop effective navigation and motion control algorithms for autonomous wheeled mobile robots （AWMR） in rough terrain. A model and analysis of relationship among wheel slippage （S）, rotation angle （0）, sinkage （z） and wheel radius （r） are presented. It is found that wheel rotation angle, sinkage and radius have some influence on wheel slippage. A multi-objective optimization problem with slippage as utility function was formulated and solved in MATLAB. The results reveal the optimal values of wheel-terrain parameters required to achieve optimum slippage on dry sandy terrain. A method of slippage estimation for a five-wheeled mobile robot was presented through comparing the odometric measurements of the powered wheels with those of the fifth non-powered wheel. The experimental result shows that this method is feasible and can be used for online slippage estimation in a sandy terrain.

Robust simultaneous tracking and stabilization of wheeled mobile robots not satisfying nonholonomic constraint

A robust unified controller was proposed for wheeled mobile robots that do not satisfy the ideal rolling without slipping constraint.Practical trajectory tracking and posture stabilization were achieved in a unified framework.The design procedure was based on the transverse function method and Lyapunov redesign technique.The Lie group was also introduced in the design.The left-invariance property of the nominal model was firstly explored with respect to the standard group operation of the Lie group SE(2).Then,a bounded transverse function was constructed,by which a corresponding smooth embedded submanifold was defined.With the aid of the group operation,a smooth control law was designed,which fulfills practical tracking/stabilization of the nominal system.An additional component was finally constructed to robustify the nominal control law with respect to the slipping disturbance by using the Lyapunov redesign technique.The design procedure can be easily extended to the robot system suffered from general unknown but bounded disturbances.Simulations were provided to demonstrate the effectiveness of the robust unified controller.

Adaptive trajectory tracking control of two-wheeled self-balance robot

Wheeled mobile robot is one of the well-known nonholonomic systems. A two-wheeled sell-balance robot is taken as the research objective. This paper carried out a detailed force analysis of the robot and established a non-linear dynamics model. An adaptive tracking controller for the kinematic model of a nonhotonomic mobile robot with unknown parameters is also proposed. Using control Lyapunov function （CLF）, the controller＇s global asymptotic stability has been proven. The adaptive trajectory tracking controller decreases the disturbance in the course of tracking control and enhances the real-time control characteristics. The simulation result indicated that the wheeled mobile robot tracking can be effectively controlled.

Mathematical modeling and simulation application for a wheeled mobile robot applied on pipe welding

A geometric model was built to represent the position relation of a wheeled mobile robot relative to a pipe. The relationship between the deviation of falling off for the robot and the curvature of the pipe was formulated quantitatively. Based on the relationship, a mathematical model was derived and a fuzzy control algorithm for the robot was developed. Simulations were carried out to confirm the dynamic index and the validity of the mathematical model of the fuzzy control algorithm for seam tracking of pipe welding. Experiments for pipe welding with the mobile robot were also carried out to verify the algorithm, and the results showed that the seam has a good quality with a preferable appearance of weld.

Optimum Design of Stair-Climbing Robots Using Taguchi Method

Environmental issues like pollution are major threats to human health.Many systems are developed to reduce pollution.In this paper,an optimal mobile robot design to reduce pollution in Green supply chain management system.Green supply chain management involves as similating environmentally and eco-nomically feasible solutions into the supply chain life-cycle.Smartness,advanced technologies,and advanced networks are becoming pillars of a sustainable supply chain management system.At the same time,there is much change happening in the logistics industry.They are moving towards a new logistics model.In the new model,robotic logistics has a vital role.The reasons for this change are the rapid growth of the e-commerce business and the shortage of workers.The advantages of using robotic logistics are reduction in human errors,faster delivery speed,better customer satisfaction,more safety for workers,and high workforce adaptability.A robot with rocker-bogie suspension is a six-wheeled mobile platform that has a distinctive potential to keep all wheels on the ground continuously.It has been designed to traverse rough and uneven terrain by distributing the load over its wheels equally.However,there is a limitation to achieving high-speed mobility against vertical barriers.In this research,an optimal design of product delivery wheeled robots for a sustainable supply chain system is proposed to ensure higher adaptability and maximum stability during climbing staircases.The design parameters of the proposed robot are optimized using Taguchi Method.The aim is to get a smooth trajectory of the robot’s center-of-mass.The proposed approach realizes a robot with much-improved stability which can climb over heights more than the size of the wheel(i.e.,3 times the radius of wheels).The results reveal that the modified rocker-bogie system not only increases the stair-climbing capability but also thwarts instability due to overturning of a wheel of the robot.

Design of dead reckoning system for mobile robot

A dead reckoning system for a wheeled mobile robot was designed, and the method for robot’s pose estimation in the 3D environments was presented on the basis of its rigid-body kinematic equations. After analyzing the locomotion architecture of mobile robot and the principle of proprioceptive sensors, the kinematics model of mobile robot was built to realize the relative localization. Considering that the research on dead reckoning of mobile robot was confined to the 2 dimensional planes, the locomotion of mobile robot in the 3 coordinate axis direction was thought over in order to estimate its pose on uneven terrain. Because the computing method in a plane is rather mature, the calculation in height direction is emphatically represented as a key issue. With experimental results obtained by simulation program and robot platform, the position of mobile robot can be reliably estimated and the localization precision can be effectively improved, so the effectiveness of this dead reckoning system is demonstrated.

Novel Algorithm for Mobile Robot Path Planning in Constrained Environment

This paper presents a development of a novel path planning algorithm, called Generalized Laser simulator (GLS), for solving the mobilerobot path planning problem in a two-dimensional map with the presence ofconstraints. This approach gives the possibility to find the path for a wheelmobile robot considering some constraints during the robot movement inboth known and unknown environments. The feasible path is determinedbetween the start and goal positions by generating wave of points in alldirection towards the goal point with adhering to constraints. In simulation,the proposed method has been tested in several working environments withdifferent degrees of complexity. The results demonstrated that the proposedmethod is able to generate efficiently an optimal collision-free path. Moreover,the performance of the proposed method was compared with the A-star andlaser simulator (LS) algorithms in terms of path length, computational timeand path smoothness. The results revealed that the proposed method hasshortest path length, less computational time and the best smooth path. Asan average, GLS is faster than A∗ and LS by 7.8 and 5.5 times, respectivelyand presents a path shorter than A∗ and LS by 1.2 and 1.5 times. In orderto verify the performance of the developed method in dealing with constraints, an experimental study was carried out using a Wheeled Mobile Robot(WMR) platform in labs and roads. The experimental work investigates acomplete autonomous WMR path planning in the lab and road environmentsusing a live video streaming. Local maps were built using data from a live video streaming with real-time image processing to detect segments of theanalogous-road in lab or real-road environments. The study shows that theproposed method is able to generate shortest path and best smooth trajectoryfrom start to goal points in comparison with laser simulator.

Kinematics Modeling of an Omnidirectional Autonomous Mobile Robot with Castor Wheels

The kinematics model of an omnidirectional wheeled mobile robot （WMR） platform with 3 castor wheels was built, which includes the actuated inverse solution and the sensed forward solution. Motion simulations verify the consistency between the actuated inverse solution and the sensed forward solution. Analysis results show that the WMR possesses 3 degrees of freedom, and its motion trajectory is a straight line. The ＂pushing＂ and ＂pulling＂ motion patterns of the WMR can be generated by using different wheel orientations. It can be used in the places where the space is limited.

Impulsive dynamics and stabilization of a single wheel robot

The impulsive motion of a dynamically stabilized robot—Gyrover, which is a single-wheel gyroscopically stabilized robot is studied. A method based on the D’Alembert-Lagrange principle is proposed to develop the impulsive dynamic model of the single wheel robot. This method that can be used to find ways to investigate a single wheel mobile robot rolling on a rough terrain is tested using the experimental platform Gyrover. The conditions of falling over without actuators are addressed. Simulations that validate the analysis are provided as well.

Data-driven iterative learning trajectory tracking control for wheeled mobile robot under constraint of velocity saturation

Considering the wheeled mobile robot(WMR)tracking problem with velocity saturation,we developed a data‐driven iterative learning double loop control method with constraints.First,the authors designed an outer loop controller to provide virtual velocity for the inner loop according to the position and pose tracking error of the WMR kinematic model.Second,the authors employed dynamic linearisation to transform the dynamic model into an online data‐driven model along the iterative domain.Based on the measured input and output data of the dynamic model,the authors identified the parameters of the inner loop controller.The authors considered the velocity saturation constraints;we adjusted the output velocity of the WMR online,providing effective solutions to the problem of velocity saltation and the saturation constraint in the tracking process.Notably,the inner loop controller only uses the output data and input of the dynamic model,which not only enables the reliable control of WMR trajectory tracking,but also avoids the influence of inaccurate model identification processes on the tracking performance.The authors analysed the algorithm's convergence in theory,and the results show that the tracking errors of position,angle and velocity can converge to zero in the iterative domain.Finally,the authors used a simulation to demonstrate the effectiveness of the algorithm.

A Wheeled Wall-Climbing Robot with Bio-Inspired Spine Mechanisms

This paper presents a wheeled wall-climbing robot with the ability to climb concrete, brick walls using circular arrays of miniature spines located around the wheel. The robot consists of two driving wheels and a flexible tail, just like letter “T”, so it is called Tbot. The simple and effective structure of Tbot enables it to be steerable and to transition from horizontal to vertical surfaces rapidly and stably. Inspired by the structure and mechanics of the tarsal chain in the Serica orientalis Motschulsky, a compliant spine mechanism was developed. With the bio-inspired compliant spine mechanism, the climbing performance of Tbot was improved. It could climb on 100° （10° past vertical） brick walls at a speed of 10 cm·s^-1. A mechanical model is also presented to analyze the forces acting on spine during a climbing cycle as well as load share between multi-spines. The simu- lation and experiment results show that the mechanical model is suitable and useful in the optimum design of Tbot.

Control of a 6DOF Mobile Manipulator with Object Detection and Tracking Using Stereo Vision

A supportive mobile robot for assisting the elderly is an emerging requirement mainly in countries like Japan where population ageing become relevant in near future.Falls related injuries are considered as a critical issue when taking into account the physical health of older people.A personal assistive robot with the capability of picking up and carrying objects for long/short distances can be used to overcome or lessen this problem.Here,we design and introduce a 3 D dynamic simulation of such an assistive robot to perform pick and place of objects through visual recognition.The robot consists of two major components;a robotic arm or manipulator to do the pick and place,and an omnidirectional wheeled robotic platform to support mobility.Both components are designed and operated according to their kinematics and dynamics and the controllers are integrated for the combined performance.The objective was to improve the accuracy of the robot at a considerably high speed.Designed mobile manipulator has been successfully tested and simulated with a stereo vision system to perform object recognition and tracking in a virtual environment resembling aroom of an elderly care.The tracking accuracy of the mobile manipulator at an average speed of 0.5 m/s is 90%and is well suited for the proposed application.

Neural Network Based Terminal Sliding Mode Control for WMRs Affected by an Augmented Ground Friction With Slippage Effect

Wheeled mobile robots(WMRs) encounter unavoidable slippage especially on the low adhesion terrain such that the robots stability and accuracy are reduced greatly.To overcome this drawback,this article presents a neural network(NN) based terminal sliding mode control(TSMC) for WMRs where an augmented ground friction model is reported by which the uncertain friction can be estimated and compensated according to the required performance.In contrast to the existing friction models,the developed augmented ground friction model corresponds to actual fact because not only the effects associated with the mobile platform velocity but also the slippage related to the wheel slip rate are concerned simultaneously.Besides,the presented control approach can combine the merits of both TSMC and radial basis function(RBF) neural networks techniques,thereby providing numerous excellent performances for the closed-loop system,such as finite time convergence and faster friction estimation property.Simulation results validate the proposed friction model and robustness of controller;these research results will improve the autonomy and intelligence of WMRs,particularly when the mobile platform suffers from the sophisticated unstructured environment.

Tracking Control of Wheeled Mobile Robots with Communication Delay and Data Loss

This paper considers the tracking control problem of a wheeled mobile robot under situation of communication delay and consecutive data packet dropouts in the feedback channel. A tracking controller in discrete-time domain for the case of ideal network condition is first derived, and then the networked predictive controller as well as two algorithms for dealing with communication delay and consecutive data packet dropouts are proposed. Simulation and experimental results verify the realizability and effectiveness of the proposed algorithms.

Modeling and multiobjective optimization of traction performance for autonomous wheeled mobile robot in rough terrain

Application of terrain-vehicle mechanics for determination and prediction of mobility performance of autonomous wheeled mobile robot （AWMR） in rough terrain is a new research area currently receiving much attention for both terrestrial and planetary missions due to its significant role in design, evaluation, optimization, and motion control of AWMRs. In this paper, decoupled closed form terramechanics considering important wheel-terrain parameters is applied to model and predict traction. Numerical analysis of traction performance in terms of drawbar pull, tractive efficiency, and driving torque is carried out for wheels of different radii, widths, and lug heights, under different wheel slips. Effects of normal forces on wheels are analyzed. Results presented in figures are discussed and used to draw some conclusions. Furthermore, a multiobjective optimization （MOO） method for achieving optimal mobility is presented. The MOO problem is formulated based on five independent variables in- eluding wheel radius r, width b, lug height h, wheel slip s, and wheel rotation angle 0 with three objectives to maximize drawbar pull and tractive efficiency while minimizing the dynamic traction ratio. Genetic algorithm in MATLAB is used to obtain opti- mized wheel design and traction control parameters such as drawbar pull, tractive efficiency, and dynamic traction ratio required for good mobility performance. Comparison of MOO results with experimental results shows a good agreement. A method to apply the MOO results for online traction and mobility prediction and control is discussed.

Research on point stabilization of a wheeled mobile robot using fuzzy control optimized by GA

A point stabilization scheme of a wheeled mobile robot （WMR） which moves on uneven surface is presented by using tuzzy control. Taking the kinematics and dynamics of the vehicle into account, the fuzzy controller is employed to regulate the robot based on a kinematic nonlinear state feedback control law. Herein, the fuzzy strategy is composed of two velocity control laws which are used to adjust the speed and angular velocity, respectively. Subsequently, genetic algorithm （GA） is applied to optimize the controller parameters. Through the self-optimization, a group of optimum parameters is gotten. Simulation results are presented to show the effectiveness of the control strategy.

Longitudinal and lateral slip control of autonomous wheeled mobile robot for trajectory tracking

This research formulates a path-following control problem subjected to wheel slippage and skid and solves it using a logic-based control scheme for a wheeled mobile robot （WMR）. The novelty of the proposed scheme lies in its methodology that considers both longitudinal and lateral slip components. Based on the derived slip model, the controller for longitudinal motion slip has been synthesized. Various control parameters have been studied to investigate their effects on the performance of the controller resulting in selection of their optimum values. The designed controller for lateral slip or skid is based on the proposed side friction model and skid check condition. Considering a car-like WMR, simulation results demonstrate the effectiveness of the proposed control scheme. The robot successfully followed the desired circular trajectory in the presence of wheel slippage and skid. This research finds its potential in various applications involving WMR navigation and control.