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.

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.

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.

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.

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.

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.

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.

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).

Design and experiment of visual navigated UGV for orchard based on Hough matrix and RANSAC

The objective of this study was to develop a visual navigation system capable of navigating an unmanned ground vehicle(UGV)travelling between tree rows in the outdoor orchard.Thus far,while most research has developed algorithms that deal with ground structures in the orchard,this study focused on the background of canopy plus sky to eliminate the interference factors such as inconsistent lighting,shadows,and color similarities in features.Aiming at the problem that the traditional Hough transform and the least square method are difficult to be applied under outdoor conditions,an algorithm combining Hough matrix and random sample consensus(RANSAC)was proposed to extract the navigation path.In the image segmentation stage,this study used an H-component that was adopted to extract the target path of the canopy plus sky.Then,after denoising and smoothing the image by morphological operation,line scanning was used to determine the midpoint of the target path.For navigation path extraction,this study extracted the feature points through Hough matrix to eliminate the redundant points,and RANSAC was used to reduce the impact of the noise points caused by different canopy shapes and fit the navigation path.The path acquisition experiment proved that the accuracy of Hough matrix and RANSAC method was 90.36%-96.81%and the time consumption of the program was within 0.55 s under different sunlight intensities.This method was superior to the traditional Hough transform in real-time and accuracy,and had higher accuracy,slightly worse real-time compared with the least square method.Furthermore,the OPENMV was used to capture the ground information of the orchard.The experiment proved that the recognition rate of OPENMV for identifying turning information was 100%,and the program running time was 0.17-0.19 s.Field experiments showed that the UGV could autonomously navigate the rows with a maximum lateral error of 0.118 m and realize the automatic turning of the UGV.The algorithm satisfied the practical operation requirements of autonomous vehicles in the orchard.So the UGV has the potential to guide multipurpose agricultural vehicles in outdoor orchards in the future.