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.

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.

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.

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.

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.

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.

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.

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.

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.

Wheeled jumping robot by powermodulation using twisted string lever mechanism

This study introduces a wheeled robot platform with jumping ability.To realize jump movement,a twisted string lever mechanism is used,which is characterized by its compactness and variable gear ratio.Based on robot modeling and parameter calculation,the twisted string actuator shows its advantage when applied to situations such as jumping of robots,where explosiveness of output force matters.In this study,a wheeled bipedal robot equipped with the twisted string actuator is designed and fabricated.It weighs 16.0 kg and can perform jumps when it encounters obstacles.The prototype can jump up to a stage with a maximum height of 1.0 m using electric power,which is approximately 1.5 times the height of its stretched legs.

Dual-mode dynamic window approach to robot navigation with convergence guarantees

In this paper,a novel,dual-mode model predictive control framework is introduced that combines the dynamic window approach to navigation with generic path planning techniques through a dual-mode model predictive control framework.The planned path adds information on the connectivity of the free space to the obstacle avoidance capabilities of the dynamic window approach.This allows for guaranteed convergence to a goal location while navigating through an unknown environment at relatively high speeds.The framework is applied in a combined simulation/hardware implementation to demonstrate the computational feasibility and the ability to cope with the constraints of a dynamic system.

Design and control of a robotic system with legs,wheels,and a reconfigurable arm

Unmanned robotic systems are expected to liberate people from heavy,monotonous,and dangerous work.However,it is still difficult for robots to work in complicated environments and handle diverse tasks.To this end,a robotic system with four legs,four wheels,and a reconfigurable arm is designed.Special attention has been given to making the robot compact,agile,and versatile.Firstly,by using separate wheels and legs,it removes the coupling in the traditional wheeled–legged system and guarantees highly efficient locomotion in both the wheeled and legged modes.Secondly,a leg–arm reconfiguration design is adopted to extend the manipulation capability of the system,which not only reduces the total weight but also allows for dexterous manipulation and multi-limb cooperation.Thirdly,a multi-task control strategy based on variable configurations is proposed for the system,which greatly enhances the adaptability of the robot to complicated environments.Experimental results are given,which validate the effectiveness of the system in mobility and operation capability.

Motion Coordination for a Class of Multi-Agents via Networked Predictive Control

The motion coordination formation control problem for a class of non-linear system is considered in this paper,where networked induced time-delays exist in the feedback channel of each agent and in communication channels between agents.As a foundation work,a coordination formation controller in discrete-time domain that without time-delay is provided firstly.Based on the above results,a motion coordination predictive formation control strategy as well as its detail implementation processes are proposed to actively compensate the time-delays.Stability analysis and simulation results are provided to demonstrate the feasibility and effectiveness of the proposed predictive strategy.

Voltage control strategy for an uncertain mobile robot

Purpose–The uncertainty and nonlinearity are the challenging problems for the control of a nonholonomic wheeled mobile robot.To overcome these problems,many valuable methods have been proposed by using two control loops namely the kinematic control and the torque control so far.In majority of the proposed approaches the dynamics of actuators is omitted for simplicity in the control design.This drawback degrades the control performance in high-velocity tracking control.On the other hand,to guarantee stability and overcome uncertainties,the control methods become computationally extensive and may be impractical due to using all states.The purpose of this paper is to design a simple controller with guaranteed stability for overcoming the nonlinearity,uncertainty and actuator dynamics.Design/methodology/approach–The control design includes two control loops,the kinematic control loop and the novel dynamic control loop.The dynamic control loop uses the voltage control strategy instead of the torque control strategy.Feedbacks of the robot orientation,robot position,robot linear and angular velocity,and motor currents are given to the control system.Findings–To improve the precision,the dynamics of motors are taken into account.The most important advantages of the proposed control law is that it is free from the robot dynamics,thereby the controller is simple,fast response and robust with ignorable tracking error.The control approach is verified by stability analysis.Simulation results show the effectiveness of the proposed control applied on an uncertain nonholonomic wheeled mobile robot driven by permanent magnet dc motors.A comparison with an adaptive sliding-mode dynamic control approach confirms the superiority of the proposed approach in terms of precision,simplicity of design and computations.Originality/value–The originality of the paper is to present a new control design for an uncertain nonholonomic wheeled mobile robot by using voltage control strategy in replace of the torque control strategy.In addition,a novel state-space model of electrically driven nonholonomic wheeled mobile robot in the workspace is presented.

Robust Exponential Stabilization of Nonholonomic Chained Systems with Unknown Parameters

The exponential stabilization problem of a robot-camera system with unknown camera parameters is investigated. Based on the visual feedback and the state-input transformation, an uncertain chained form model is presented for a type of nonholonomic mobile robots. Then, a new time-varying feedback controller is proposed to stabilize the uncertain system exponentially with the help of the stabilization theorems, state-scaling and switching techniques. The exponential stability of the closed-loop system is rigorously proved. Simulation results are given to demonstrate the effectiveness of the proposed strategies.