Observer-Based Path Tracking Controller Design for Autonomous Ground Vehicles With Input Saturation

This paper investigates the problem of path tracking control for autonomous ground vehicles(AGVs),where the input saturation,system nonlinearities and uncertainties are considered.Firstly,the nonlinear path tracking system is formulated as a linear parameter varying(LPV)model where the variation of vehicle velocity is taken into account.Secondly,considering the noise effects on the measurement of lateral offset and heading angle,an observer-based control strategy is proposed,and by analyzing the frequency domain characteristics of the derivative of desired heading angle,a finite frequency H_∞index is proposed to attenuate the effects of the derivative of desired heading angle on path tracking error.Thirdly,sufficient conditions are derived to guarantee robust H_∞performance of the path tracking system,and the calculation of observer and controller gains is converted into solving a convex optimization problem.Finally,simulation examples verify the advantages of the control method proposed in this paper.

Study on shift schedule saving energy of automatic transmission of ground vehicles

To improve ground vehicle efficiency, shift schedule energy saving was proposed for the ground vehicle automatic transmission by studying the function of the torque converter and transmission in the vehicular drivetrain. The shift schedule can keep the torque converter working in the high efficiency range under all the working conditions except in the low efficiency range on the left when the transmission worked at the lowest shift, and in the low efficiency range on the right when the transmission worked at the highest shift. The shift quality key factors were analysed. The automatic trans-mission's bench-test adopting this shift schedule was made on the automatic transmission's test-bed. The experimental results showed that the shift schedule was correct and that the shift quality was controllable.

Ribbon model based path tracking method for autonomous ground vehicles

To resolve the path tracking problem of autonomous ground vehicles,an analysis of existing path tracking methods was carried out and an important conclusion was got.The vehicle-road model is crucial for path following.Based on the conclusion,a new vehicle-road model named "ribbon model" was constructed with consideration of road width and vehicle geometry structure.A new vehicle-road evaluation algorithm was proposed based on this model,and a new path tracking controller including a steering controller and a speed controller was designed.The difficulties of preview distance selection and parameters tuning with speed in the pure following controller are avoided in this controller.To verify the performance of the novel method,simulation and real vehicle experiments were carried out.Experimental results show that the path tracking controller can keep the vehicle in the road running as fast as possible,so it can adjust the control strategy,such as safety,amenity,and rapidity criteria autonomously according to the road situation.This is important for the controller to adapt to different kinds of environments,and can improve the performance of autonomous ground vehicles significantly.

An Ellipsoidal Set-Membership Approach to Distributed Joint State and Sensor Fault Estimation of Autonomous Ground Vehicles

This paper is concerned with the problem of distributed joint state and sensor fault estimation for autonomous ground vehicles subject to unknown-but-bounded(UBB)external disturbance and measurement noise.In order to improve the estimation reliability and performance in cases of poor data collection and potential communication interruption,a multisensor network configuration is presented to cooperatively measure the vehicular yaw rate,and further compute local state and fault estimates.Toward this aim,an augmented descriptor vehicle model is first established,where the unknown sensor fault is modeled as an auxiliary state of the system model.Then,a new distributed ellipsoidal set-membership estimation approach is developed so as to construct an optimized bounding ellipsoidal set which guarantees to contain the vehicle’s true state and the sensor fault at each time step despite the existence of UBB disturbance and measurement noises.Furthermore,a convex optimization algorithm is put forward such that the gain matrix of each distributed estimator can be recursively obtained.Finally,simulation results are provided to validate the effectiveness of the proposed approach.

Communication security of autonomous ground vehicles based on networked control systems:The optimized LMI approach

The paper presents a study of networked control systems(NCSs)that are subjected to periodic denial-of-service(DoS)attacks of varying intensity.The use of appropriate Lyapunov-Krasovskii functionals(LKFs)help to reduce the constraints of the basic conditions and lower the conservatism of the criteria.An optimization problem with constraints is formulated to select the trigger threshold,which is solved using the gradient descent algorithm(GDA)to improve resource utilization.An intelligent secure event-triggered controller(ISETC)is designed to ensure the safe operation of the system under DoS attacks.The approach is validated through experiments with an autonomous ground vehicle(AGV)system based on the Simulink platform.The proposed method offers the potential for developing effective defense mechanisms against DoS attacks in NCSs.

A survey on multi-sensor fusion based obstacle detection for intelligent ground vehicles in off-road environments

With the development of sensor fusion technologies, there has been a lot of research on intelligent ground vehicles, where obstacle detection is one of the key aspects of vehicle driving. Obstacle detection is a complicated task, which involves the diversity of obstacles, sensor characteristics, and environmental conditions. While the on-road driver assistance system or autonomous driving system has been well researched, the methods developed for the structured road of city scenes may fail in an off-road environment because of its uncertainty and diversity.A single type of sensor finds it hard to satisfy the needs of obstacle detection because of the sensing limitations in range, signal features, and working conditions of detection, and this motivates researchers and engineers to develop multi-sensor fusion and system integration methodology. This survey aims at summarizing the main considerations for the onboard multi-sensor configuration of intelligent ground vehicles in the off-road environments and providing users with a guideline for selecting sensors based on their performance requirements and application environments.State-of-the-art multi-sensor fusion methods and system prototypes are reviewed and associated to the corresponding heterogeneous sensor configurations. Finally, emerging technologies and challenges are discussed for future study.

Model predictive control for autonomous ground vehicles:a review

This paper reviews model predictive control(MPC)and its wide applications to both single and multiple autonomous ground vehicles(AGVs).On one hand,MPC is a well-established optimal control method,which uses the predicted future information to optimize the control actions while explicitly considering constraints.On the other hand,AGVs are able to make forecasts and adapt their decisions in uncertain environments.Therefore,because of the nature of MPC and the requirements of AGVs,it is intuitive to apply MPC algorithms to AGVs.AGVs are interesting not only for considering them alone,which requires centralized control approaches,but also as groups of AGVs that interact and communicate with each other and have their own controller onboard.This calls for distributed control solutions.First,a short introduction into the basic theoretical background of centralized and distributed MPC is given.Then,it comprehensively reviews MPC applications for both single and multiple AGVs.Finally,the paper highlights existing issues and future research directions,which will promote the development of MPC schemes with high performance in AGVs.

Multi-constrained model predictive control for autonomous ground vehicle trajectory tracking

A multi-constrained model predictive control （ MPC ） algorithm for trajectory tracking of an autonomous ground vehicle is proposed and tested in this paper. First, to simplify the computa- tion, an active steering linear error model is applied in the MPC controller. Then, a control incre- ment constraint and a relaxing factor are taken into account in the objective function to ensure the smoothness of the trajectory, using a softening constraints technique. In addition, the controller can obtain optimal control sequences which satisfy both the actual kinematic constraints and the actuator constraints. The circular trajectory tracking performance of the proposed method is compared with that of another MPC controller. To verify the trajectory tracking capabilities of the designed control- ler at different desired speed, the simulation experiments are carried out at the speed of 3m/s, 5m/ s and 10m/s. The results demonstrate the MPC controller has a good speed adaptability.

Modeling and control for hydraulic transmission of unmanned ground vehicle

Variable pump driving variable motor(VPDVM) is the future development trend of the hydraulic transmission of an unmanned ground vehicle(UGV).VPDVM is a dual-input single-output nonlinear system with coupling,which is difficult to control.High pressure automatic variables bang-bang(HABB) was proposed to achieve the desired motor speed.First,the VPDVM nonlinear mathematic model was introduced,then linearized by feedback linearization theory,and the zero-dynamic stability was proved.The HABB control algorithm was proposed for VPDVM,in which the variable motor was controlled by high pressure automatic variables(HA) and the variable pump was controlled by bang-bang.Finally,simulation of VPDVM controlled by HABB was developed.Simulation results demonstrate the HABB can implement the desired motor speed rapidly and has strong robustness against the variations of desired motor speed,load and pump speed.

Telepresence Robots and Controlling Techniques in Healthcare System

In this era of post-COVID-19,humans are psychologically restricted to interact less with other humans.According to the world health organization(WHO),there are many scenarios where human interactions cause severe multiplication of viruses from human to human and spread worldwide.Most healthcare systems shifted to isolation during the pandemic and a very restricted work environment.Investigations were done to overcome the remedy,and the researcher developed different techniques and recommended solutions.Telepresence robot was the solution achieved by all industries to continue their operations but with almost zero physical interaction with other humans.It played a vital role in this perspective to help humans to perform daily routine tasks.Healthcare workers can use telepresence robots to interact with patients who visit the healthcare center for initial diagnosis for better healthcare system performance without direct interaction.The presented paper aims to compare different telepresence robots and their different controlling techniques to perform the needful in the respective scenario of healthcare environments.This paper comprehensively analyzes and reviews the applications of presented techniques to control different telepresence robots.However,our feature-wise analysis also points to specific technical,appropriate,and ethical challenges that remain to be solved.The proposed investigation summarizes the need for further multifaceted research on the design and impact of a telepresence robot for healthcare centers,building on new perceptions during the COVID-19 pandemic.

The future and technique challenges of high-speed ground effect vehicle enrolled in maritime transportation

This paper presents a high-speed ground effect vehicle(HS-GEV)used specifically for maritime transportation.Given the limitations of current vessels,including various types of watercraft and high-speed boats,in fulfilling of needs in different maritime transportation scenarios,the HS-GEV emerges as a promising solution to address unmet requirements.To efficiently accomplish maritime transportation missions with quickness and safety,several critical features are emphasized,including short take-off on water,flight maneuverability and flight stability.The key techniques required to achieve these features,as well as recent progress highlights,are introduced.Following and promoting these crucial techniques is also suggested as a future step to improve HS-GEV performance.With its predominant features,the HS-GEV holds immense application value in enhancing a high-speed maritime transportation system that aligns with the evolving needs of the real world.

Filtering algorithm of line structured light for long-distance obstacle detection

Since unmanned ground vehicles often encounter concave and convex obstacles in wild ground, a filtering algorithm using line structured light to detect these long distance obstacles is proposed. For the line structured light image, a ranked-order based adaptively extremum median （RAEM） filter algorithm on salt and pepper noise is presented. In the algorithm, firstly effective points and noise points in a filtering window are differentiated; then the gray values of noise points are replaced by the medium of gray values of the effective pixels, with the efficient points＇ gray values unchanged; in the end this algorithm is proved to be efficient by experiments. Experimental resuits demonstrate that the image blur, resulting into proposed algorithm can remove noise points effectively and minimize the protecting the edge information as much as possible.

Experimental and Numerical Study of Wind Noise Caused by Cowl Area on Volvo XC60

This paper presents a detailed experimental and numerical study of aerodynamically produced noise which occurs due to turbulent structures created by the cowl cavity and side mirror. Measurements were carried out at Volvo aerodynamical wind tunnel on a Volvo XC60 production model. The configurations considered here are： side mirror On/Off with the cowl cavity open/closed. The results of exterior sound source mapping （with the intensity probe placed in the flow stream） have been compared with the results of the measurements inside the car. The contribution of the cowl area to overall wind noise level is measured in terms of AI% （Articulation Index） inside the compartment. It was shown that increase in AI by 2% could be attributed to the cowl generated wind noise. Transient numerical simulations of the turbulent flow around the car have been performed for all configurations. The results of the simulations show similarity to experimental results and give insight to the flow structures around the car.

IoT-Enabled Autonomous System Collaboration for Disaster-Area Management

Timely investigating post-disaster situations to locate survivors and secure hazardous sources is critical,but also very challenging and risky.Despite first responders putting their lives at risk in saving others,human-physical limits cause delays in response time,resulting in fatality and property damage.In this paper,we proposed and implemented a framework intended for creating collaboration between heterogeneous unmanned vehicles and first responders to make search and rescue operations safer and faster.The framework consists of unmanned aerial vehicles(UAVs),unmanned ground vehicles(UGVs),a cloud-based remote control station(RCS).A light-weight message queuing telemetry transport(MQTT)based communication is adopted for facilitating collaboration between autonomous systems.To effectively work under unfavorable disaster conditions,antenna tracker is developed as a tool to extend network coverage to distant areas,and mobile charging points for the UAVs are also implemented.The proposed framework’s performance is evaluated in terms of end-to-end delay and analyzed using architectural analysis and design language(AADL).Experimental measurements and simulation results show that the adopted communication protocol performs more efficiently than other conventional communication protocols,and the implemented UAV control mechanisms are functioning properly.Several scenarios are implemented to validate the overall effectiveness of the proposed framework and demonstrate possible use cases.

Unmanned Drug Delivery Vehicle for COVID-19 Wards in Hospitals

The prime reason for proposing the work is designing and developing a low-cost guided wireless Unmanned Ground Vehicle(UGV)for use in hospitals for assistance in contactless drug delivery in COVID-19 wards.The Robot is designed as per the requirements and technical specifications required for the healthcare facility.After a detailed survey and tests of various mechanisms for steering and structure of UGV,the best mechanism preferred for steering articulated and for body structure is hexagonal as this approach provides decent performance and stability required to achieve the objective.The UGV has multiple sensors onboard,such as a Camera,GPS module,Hydrogen,and Carbon Gas sensor,Raindrop sensor,and an ultrasonic range finder on UGV for the end-user to understand the circumferential environment and status of UGV.The data and control options are displayed on any phone or computer present in the Wi-Fi zones only if the user login is validated.ESP-32 microcontroller is the prime component utilized to establish reliable wireless communication between the user and UGV.These days,the demand for robot vehicles in hospitals has increased rapidly due to pandemic outbreaks as using this makes a contactless delivery of the medicinal drug.These systems are designed specifically to assist humans in the current situation where life can be at risk for healthcare facilities.In addition,the robot vehicle is suitable for many other applications like supervision,sanitization,carrying medicines and medical equipment for delivery,delivery of food and used dishes,laundry,garbage,laboratory samples,and additional supply.

Integrated sensor system for monitoring rice growth conditions based on unmanned ground vehicle system

Ground-based platform systems provide a good tool for monitoring and managing crop conditions in precision agriculture applications and have been widely used for monitoring crop conditions.To develop an unmanned ground vehicle system(UGVS)based multi-sensors and test the feasibility of this system for monitoring rice conditions,an UGVS was developed to collect real-time rice condition information including NDVI values,reflectance measurements and crop canopy temperature in this study.Major components of the integrated system are GreenSeeker R100 system,hyper-spectroradiometer and infrared temperature sensor.The leaf area index(LAI)was measured by the CGMD302 Spectrometer.The Independent Samples T-Test method and the one way ANOVA method were used to determine the best spectral indices and analyze the relationship between the vegetation indices and rice LAI.It was found that the two best spectral indices for estimating LAI were NDVI(860 nm and 750 nm)with the correlation coefficient(R^(2))at 0.745 and RVI(853 nm and 751 nm)with the R^(2)at 0.724.The results show the UGVS can support multi-source information acquisition and is useful for crop management and precision agriculture applications.

A Rapid Path Planner for Autonomous Ground Vehicle Using Section Collision Detection

Rapid path planner plays an important role in autonomous ground vehicle （AGV） operation. Depending on the non-holonomic kinematics constraints of AGV, its path planning problem is discussed. Since rapidly-exploring random tree （RRT） can directly take non-holonomic constraints into consideration, it is selected to solve this problem. By applying extra constraints on the movement, the generation of new configuration in RRT algorithm is simplified and accelerated. With section collision detection method applied, collision detection within the planer becomes more accurate and efficient. Then a new path planner is developed. This method complies with the non-holonomic constraints, avoids obstacles effectively and can be rapidly carried out while the vehicle is running. Simulation shows that this path planner can complete path planning in less than 0.5 s for a 170 mx 170 m area with moderate obstacle complexity.

Motion control design for unmanned ground vehicle in dynamic environment using intelligent controller

Purpose–The motion control of unmanned ground vehicles(UGV)is a challenge in the industry of automation.The purpose of this paper is to propose a fuzzy inference system(FIS)based on sensory information for solving the navigation challenge of UGV in cluttered and dynamic environments.Design/methodology/approach–The representation of the dynamic environment is a key element for the operational field and for the testing of the robotic navigation system.If dynamic obstacles move randomly in the operation field,the navigation problem becomes more complicated due to the coordination of the elements for accurate navigation and collision-free path within the environmental representations.This paper considers the construction of the FIS,which consists of two controllers.The first controller uses three sensors based on the obstacles distances from the front,right and left.The second controller employs the angle difference between the heading of the vehicle and the targeted angle to obtain the optimal route based on the environment and reach the desired destination with minimal running power and delay.The proposed design shows an efficient navigation strategy that overcomes the current navigation challenges in dynamic environments.Findings–Experimental analyses are conducted for three different scenarios to investigate the validation and effectiveness of the introduced controllers based on the FIS.The reported simulation results are obtained using MATLAB software package.The results show that the controllers of the FIS consistently perform the manoeuvring task and manage the route plan efficiently,even in a complex environment that is populated with dynamic obstacles.The paper demonstrates that the destination was reached optimally using the shortest free route.Research limitations/implications–The paper represents efforts toward building a dynamic environment filled with dynamic obstacles that move at various speeds and directions.The methodology of designing the FIS is accomplished to guide the UGV to the desired destination while avoiding collisions with obstacles.However,the methodology is approached using two-dimensional analyses.Hence,the paper suggests several extensions and variations to develop a three-dimensional strategy for further improvement.Originality/value–This paper presents the design of a FIS and its characterizations in dynamic environments,specifically for obstacles that move at different velocities.This facilitates an improved functionality of the operation of UGV.

Multiple UAVs/UGVs heterogeneous coordinated technique based on Receding Horizon Control (RHC) and velocity vector control

Multiple unmanned air vehicles(UAVs)/unmanned ground vehicles(UGVs) heterogeneous cooperation provides a new breakthrough for the effective application of UAV and UGV.On the basis of introduction of UAV/UGV mathematical model,the characteristics of heterogeneous flocking is analyzed in detail.Two key issues are considered in multi-UGV subgroups,which are Reynolds Rule and Virtual Leader(VL).Receding Horizon Control(RHC) with Particle Swarm Optimization(PSO) is proposed for multiple UGVs flocking,and velocity vector control approach is adopted for multiple UAVs flocking.Then,multiple UAVs and UGVs heterogeneous tracking can be achieved by these two approaches.The feasibility and effectiveness of our proposed method are verified by comparative experiments with artificial potential field method.

An improved artificial physics approach to multiple UAVs/UGVs heterogeneous coordination

This paper proposed an improved artificial physics(AP)method to solve the autonomous navigation problem for multiple unmanned aerial vehicles(UAVs)/unmanned ground vehicles(UGVs)heterogeneous coordination in the three-dimensional space.The basic AP method has a shortcoming of easily plunging into a local optimal solution,which can result in navigation fails.To avoid the local optimum,we improved the AP method with a random scheme.In the improved AP method,random forces are used to make heterogeneous multi-UAVs/UGVs escape from local optimum and achieve global optimum.Experimental results showed that the improved AP method can achieve smoother trajectories and smaller time consumption than the basic AP method and basic potential field method(PFM).