Robotic Vehicle Research Articles

Finite-time robust formation control of multiple aerial robotic vehicles with uncertainties and time-varying complex perturbations

Formation control of aerial robotic vehicles (ARVs) has a wide range of applications in the battlefield reconnaissance, medical rescue and load transportation, etc. System parameter variations and complex disturbances are inevitable in the formation control of ARVs, and the effects of them on the formation stability control of ARVs are unnegligible. This paper addresses the robust formation control problem of finite-time leader–follower for multiple ARVs suffering from parameter uncertainties and time-varying perturbations. To ensure the states (e.g. position and velocity) of all followers to converge to leader in finite time, a novel finite-time high-order sliding mode consensus control (HOSMCC) scheme is designed. To better cope with the parameter uncertainties and time-varying disturbances, improve formation control accuracy and achieve the robust formation control of finite-time leader–follower in multiple ARV systems, a new finite time high-order sliding mode formation control (HOSMFC) scheme on the basis of finite-time HOSMCC is proposed. The finite-time stability of multi-ARV formation control system is guaranteed, and the desired formation pattern of multi-ARV systems is achieved using Lyapunov stability theorem. Performance comparisons with proportional differential formation controller (PDFC) and sliding mode formation controller (SMFC) are studied on a four-ARV formation control system. The results validate the designed formation control scheme.

Development of an Artificial Intelligence based Railway Crack Detection and Monitoring System using Internet of Things

This study suggests the concept of crack locating robot vehicle in the railway rails. India railways participates an important posture in asset with the necessary transportation to preserve needs of a rapidly emergent financial system. India now has the world's fourth-largest railway network. Therefore, travelling by train is risky. It does not work with the existing railway control system in India. Thus, robust, well-organized, and reliable new technology is required for both fracture detection in railway track and identification of objector items. This study proposes and clarifies a robust monitoring system to meet the limitations of the current rail surveillance system for detecting fractures of the railway tracks. Therefore, robust, well-organized, and reliable new technology is required for both fracture detection in railway track and the identification of objects or items. This study proposes and clarifies a robust monitoring system to meet the limitations of the current rail surveillance system for detecting fractures of the railway tracks. The goal of this study is to build and create an IoT-enabled robot that uses artificial intelligence (AI) to report to a railway controller any information it gathers concerning broken or cracked track. To solve this issue, we will be sending all data over wireless communication based devices and developing a corresponding application..

Design and simulation of a 3D-printed wall-climbing robot for high-risk construction tasks

This study aims to design and calculate a model for a wall-climbing robot to replace humans in performing dangerous tasks at great heights in construction sites. The research simultaneously addresses three main issues in the process of calculation, design, and simulation of the vertically climbing robot model. Firstly, the study conducts calculations and analyzes the dynamics of the model in various working states. Specifically, it calculates the suction force of the fan in non-contact conditions to ensure the suction capability of the model during practical operations. Secondly, the core content of this method involves utilizing the airflow generated by the engine through a specially designed suction mechanism to increase the airflow velocity significantly, thus creating a low-pressure area capable of adhering to the wall. This suction force calculation method and other forces acting on the robot model are based on numerical simulation software. The boundary conditions in the calculation process for the wall-climbing robot model are derived from the tasks that the robot performs during real operations, replacing humans. Thirdly, the study designs the wall-climbing robot using the non-contact suction force method through a 3D-printed fan model to enhance the model’s durability and optimize the airflow under various conditions. In summary, through this research, the paper aims to construct a robot model using non-contact suction and complete it entirely with 3D printing technology. This model will generate cost-effective and highly efficient robot vehicles that can be widely applied in modern industrial environments.

Smart Voice Controlled Obstacle Avoiding Robotic Car

The project is about building a Multifunctional Robot with Obstacle Avoidance Robotic Vehicle using Ultrasonic sensors for its movement and Bluetooth control through manual or voice commands. A Microcontroller (ATmega328P) is used to achieve the desired operation. A Robot is a machine that can perform task automatically or with guidance. The project proposes robotic vehicle that has an intelligence built in it such that it directs itself whenever an obstacle comes in its path. This robotic vehicle is built, using a micro-controller of AT mega 328 family. An ultrasonic sensor is used to detect any obstacle ahead of it and sends a command to the micro-controller. Depending on the input signal received, the micro-controller redirects the robot to move in an alternate direction by actuating the motors which are interfaced to it through a motor driver. It has features as smart voice control by which user can give commands as left, right, front, back which gives another mode as manual operating mode.

Model predictive path-following controller for Generalised N-Trailer vehicles with noisy sensors and disturbances

Generalised N-Trailer (GNT) vehicles, commonly used in agriculture, mining, and industry, consist of a tractor pulling multiple passive trailers. This paper presents a nonlinear moving horizon estimator (NMHE) and nonlinear model predictive controller (NMPC) for GNT robotic vehicles. The NMHE accurately estimates the vehicle’s state under challenging conditions such as noisy measurements, disturbances, and different soil conditions, without relying on assumptions about disturbances, making it more effective than techniques like the Extended Kalman Filter (EKF). Similarly, the NMPC successfully steers the GNT along a predefined path with lower control effort compared to existing algorithms, thanks to smoother tractor manoeuvres that minimise energy in the objective function. Moreover, unlike other methods, this approach computes the tractors’ velocities instead of those of the last trailer, eliminating the need for kinematic inversion and making it suitable for various vehicle configurations. Efficient solvers for the NMHE and NMPC problems were generated using two different open-source frameworks. The proposed framework was evaluated through challenging simulated studies and field experiments. Additional resources, including code implementation and field experiment videos, can be found at https://drive.google.com/drive/folders/1n-qVWJA40cZn-WiDpwXhhF9AdK54LTfX?usp=sharing.

Twisting morphing wings with tight geometric constraints for biomimetic swimming or flying robotic vehicles

Active twisting morphing (ATM) wings have significant implications for biomimetic swimming or flying robotic vehicles. This article considers an ATM wing that has one shaft with many ribs, each rib is driven to swing in its individual plane that is perpendicular to the shaft, showing increasingly swing angles from the wing base to the wing-tip and thus form active wing twisting. For the overall twisting angle of the wing that is less than 90 degrees (e.g., during cruising operations of the robotic vehicles), we show that the geometry of mechanical implementations of the twisting wing can be further tightened using segment gears for transmission, instead of normal whole gears, which constraints have been largely unexplored. Here we provide the geometric constraints on the transmission with segment gears for such wing and give tighter feasible solutions of the constraints as well as provide the mechanical implementations using segment gears that are compact for ATM wings for biomimetic robotic vehicles.

Military Purpose Robot

In modern world many countries are working on different technologies. Hence, safety of soldiers and army personnel who fight for national security of their respective country need to considered. During warfare many of the soldiers lose their lives in abandoned areas or at borders. Landmines are an explosive weapon which may be or may not be buried under the soil and activated by a mere pressure of 9kg when someone steps on it. It also has an adverse effect on environment such as damage to soil structure, reducing soil productivity and increase vulnerability of soil to water and wind erosion. Mines also kill innocent civilians and soldiers after war ends. In order to save the lives of soldiers and diffuse the mines this paper is proposing a robotic vehicle with a metal detector which is capable of sensing mine ahead of it. It will also detect position of landmine and send latitude, longitude coordinates using GPS module. and also, Video surveillance is the process of monitoring a situation, an area or a person. This generally occurs in a military scenario where surveillance of borderlines and enemy territory is essential to a country’s safety. Human surveillance is achieved by deploying personnel near sensitive areas in order to constantly monitor for changes. But humans do have their limitations, and deployment in inaccessible places is not always possible. We have developed a robot which can be used for video surveillance & monitoring which can be controlled through a GUI. The control mechanism is provided with a video transmission facility. The video transmission is practically achieved through high-speed image transmission. Initially, the robot will be equipped with a camera which will capture the scenes and transfer the images to the server on which the user will be controlling and watching the live feed. Key Words: Node MCU (ESP8266), GPS Module, Metal Detector, Motor Driver (L298N), ESP32-cam module, Surveillance Robot, landmine detection, fire detection, temperature and humidity sensing.

Ride comfort of patient transport robot chassis

The ride comfort is a significant property of patient transport robots, which is directly related to the performance of rescue instruments and the cause of secondary damage. Previous studies overlook the design optimization of patient transport robots to improve ride comfort in hospital environments. This study designs a mobility system with an improved chassis that enables a more comfortable ride for patients. The system incorporates a longitudinal arm-independent suspension, which has a regulating device that changes the shock absorber angle and longitudinal arm length. A four-wheel vibration coupling response model of the robot vehicle is established. An optimization model with variable stiffness and damping coefficients is built and analyzed. The effective and maximum values of the body’s vertical, pitch angular, and roll angular accelerations are used as evaluation criteria of the robot’s ride comfort, which is analyzed on random roads and roadblocks, comparing its performance before and after the optimization. The results show that the weighted acceleration of the optimized body reduces by 61.9%, and the optimized suspension system improves the overall robot’s ride comfort. The evaluation indices of the optimized robot are measured through experiments. The weighted acceleration in the three directions of the optimized body is 0.18[Formula: see text]m/s2, which is less than 0.315[Formula: see text]m/s2 as required by ISO 2631-1, indicating that the patient does not feel uncomfortable, rendering an excellent evaluation, and verifying the rationality of the suspension system modeling analysis. The establishment of the multi-objective optimization model provides a theoretical basis for improving the ride comfort of mobile robots.

Saliency-Induced Moving Object Detection for Robust RGB-D Vision Navigation Under Complex Dynamic Environments

Localization in unknown environments is an essential requirement for vision navigation of robotic vehicles in intelligent transportation systems. However, moving objects in dynamic scenarios usually bring about great difficulty for robot localization, because motion estimation of robotic vehicles is disturbed by increasing feature outliers caused by moving objects. In order to improve the accuracy and robustness of robot localization, a novel saliency-induced moving object detection (SMOD) approach is proposed to filter out feature outliers for RGB-D-based simultaneous localization and mapping (SLAM) in complex dynamic workspaces. Firstly, three complementary motion saliency potentials, including motion energy (ME), spatiotemporal objectness (STO), and dynamic superpixels (DS), are modeled by fully analyzing spatial, temporal, appearance and depth cues in RGB-D inputs. They can be used to identify the dynamic objects effectively from diversely changing backgrounds. Then, a superpixel-level graph-based motion saliency (MS) measure is proposed to generate the MS map for reliable localization of the moving objects. The edge weights and background nodes on the graph are determined reasonably by fusing ME, STO, and DS, which is not vulnerable to background interferences. Furthermore, the SMOD approach is embedded into the front-end of ORB-SLAM3 as a pre-processing stage, in order to filter out feature outliers associated with the moving objects. Finally, the extensive experiments are performed to verify the accuracy and robustness of the proposed approach on the public dynamic datasets. The experimental results show that the SMOD method can detect the moving objects effectively in a variety of challenging dynamic environments, and separate the dynamic regions reliably from the irrelevant background. The data comparison demonstrates that the SMOD-SLAM navigation system can outperform other state-of-the-art dynamic visual SLAM (vSLAM) systems.

Object Detection Techniques: A Review

Humans can understand their surroundings clearly because they regularly notice objects in their environment. It is essential for the machine to perceive the surroundings similarly to how humans do in order to make it autonomous and capable of navigating in the human world. The machine can assess its surroundings and identify objects using object detection. This can simplify a number of tasks and enable the machine to recognize its surroundings. Making bounding boxes that surround the objects is essentially how object detection systems work to locate objects in an image. Object detection has applications such as autonomous robot navigation, surveillance, face detection, and vehicle

Advancements in Agricultural Automation: A Comprehensive Review of Artificial Intelligence and Humanoid Robotics in Farming

This paper discusses about the modern techniques implemented in the field of agriculture which shaped the traditional farming to the smart farming (Agriculture 4.0). The rapid rise in the global population is one among the main reasons, besides monitoring of crops health and yield requires a huge labor force, which is also another reason for promoting intelligent systems into agriculture sector. Conventional farming methods are not suitable to meet this demand, which led robotics to associate with on-field agriculture by means of robot-based technologies like wheeled robots, ground vehicles (manned and unmanned) and aerial vehicles (manned and unmanned) that led to explore the possible advancement in agriculture 3.0. Currently, the evolutionary techniques, such as Artificial Intelligence (AI) and IoT, are implemented in robotic vehicles to make them intelligent systems. Due to unprecedented climatic change and polluted ground water for the past few decades, the crops are being infested with new varieties of diseases. This requires new image processing techniques to classify the diseases based on color, texture and, shape of leaves. The incorporation of image processing technique into AI aids in deciding the appropriate amount of herbicide supplement to the plant based on the prediction of plant growth.

Global experience in the application of intelligent systems and technologies in the military sphere

This article analyzes technologies and modern means of military use with intelligent computer systems (platforms). Such means include "smart" bullets, rifles with augmented reality glasses, as well as ballistic computers, "smart" weapons (mortars), high-precision ammunition, robotic combat vehicles and other equipment, laser air defense systems for ground, air, as well as naval forces, unmanned aerial vehicles, etc. Examples of intellectual means of military use, their tactical and technical characteristics and fields of application are given. The advantages and disadvantages of using technologies and means with intelligent systems (platforms) are highlighted, as well as the justified expediency of their use for military purposes. The examples of tools with intelligent systems (platforms) listed above are effectively used in the leading countries of the world, namely: the USA, Great Britain, Japan, France, Germany, Israel, the Netherlands, etc. The experience of use by the military of these countries has shown that intelligent systems make it possible to simplify the performance of relevant tasks, measures to protect against accidents or excessive aggression of criminals (enemies), and also increase the safety of the civilian population. It was determined that the introduction of world achievements, as well as the development of domestic systems and means with intelligent systems, is one of the priority directions of the development of the military-industrial complex of Ukraine. This, in turn, requires close cooperation between scientists and the military, which prompts the study of the possibilities of using intelligent systems in various fields, in particular in the field of national security development of Ukraine. Further prospective studies in this direction are highlighted.

Decision Support System for autonomous vehicle maintenance management

Autonomous vehicles are complex objects equipped with the tools for monitoring the technical condition and transmitting data for diagnostics and prediction. The design of new models of autonomous and robotic vehicles is inextricably linked with the development of a maintenance system. The efficient functioning of the maintenance system is ensured by the use of intelligent technologies and digital twins. The article proposes an approach to designing a decision support system for the maintenance and repair of a fleet of autonomous vehicles. The decision support system is focused on robotic agricultural vehicles. The proposed structure of the system is of a general nature and can be used in transport and logistics enterprises in various sectors of the economy. The general architecture of the maintenance system is presented, including the neuro-digital twin of the vehicle, the analytics unit, simulation models of operation processes, and service centers. The components of the neuro-digital twin are digital twins of car units, a knowledge base, domain ontology, artificial neural networks, and a team of experts. The proposed approach is based on a combination of intelligent technologies and simulation modeling in collaboration with a team of experts. A set of original simulation models for the operation of a fleet of autonomous vehicles has been developed. New models based on stochastic timed colored Petri nets are proposed to analyze the processes during the autonomous vehicle operation. The developed decision support system can be used both at the stage of virtual commissioning and in the real operation of autonomous vehicles.

Disturbance rejection controller design based on adaptive nonlinear FOPID controller and chaotic WOA with a neuro-fuzzy approximation for URV robot

This paper presents an adaptive neuro-fuzzy-based nonlinear fractional order proportional integral derivative (ANF-NLFOPID) controller to stabilize six degrees of freedom (6-DOF) underwater robotic vehicle (URV). Generally, the stability of the URV system is jammed due to internal and external variations related to unknown uncertainties and disturbances in the URV model, which lead to trajectory tracking problems. Thus, to solve unknown uncertainties and disturbances problems, an ANF network is proposed to estimate unknown uncertainties and disturbances. At the same time, an NLFOPID controller is proposed to minimize the error effect generated by the variation of the URV model parameters. Considering the unknown and unpredictable behavior of the URV system in the presence of uncertainties and disturbances, the ANF-NLFOPID controller parameters are tuned continuously using an improved whale optimization algorithm based on chaotic theory (IWOA-CT). The main working principle of the IWOA-CT is to solve the local minimum (optimum) problem and achieve the global optimum points to deliver the best parameter values for the ANF-NLFOPID controller. A simulation and experimental results are conducted to measure the performance of the ANF-NLFOPID controller compared to other existing works. MATLAB software is used to simulate four trajectory tracking cases, where the first case proved the superiority of the ANF-NLFOPID controller by 52.559%, 70.028%, and 73.83%, the second case shows that the ANF-NLFOPID improves the trajectory tracking performance by 34.399%, 46.094%, and 59.143%, the third case demonstrates the effectiveness of the ANF-NLFOPID controller by 41.922%, 51.205%, and 62.252%, and the fourth case shows that the ANF-NLFOPID enhance the overall trajectory tracking efficiency by 29.356%, 38.413%, and 44.795% compared to adaptive neural network-based nonlinear FOPID (ANNFOPID), adaptive fuzzy-based nonlinear PID (AFNLPID), and disturbance rejection based on adaptive neural network (DR-ANN) controllers respectively. In the end, the experimental results were conducted using a real-world URV model and showed that the ANF-NLFOPID controller presents superior in solving trajectory tracking problems compared to the ANNFOPID controller.

A set-based approach for detecting faults of a remotely controlled robotic vehicle during a trajectory tracking maneuver

This paper addresses the problem of fault detection for a remotely controlled Differential Drive Mobile Robot (DDMR) during trajectory tracking maneuvers. The proposed solution involves two steps. The first step, performed offline, consists of generating a feasible trajectory for the DDMR subject to unknown but bounded external disturbances. To this end, the dynamics of the closed-loop trajectory tracking error are first described using an uncertain system with norm-bounded uncertainty. The optimal feasible trajectory is obtained by a recursive algorithm that involves solving some SDP optimization problems with LMIs constraints. In the second step, which is performed online, the feasibility property of the computed trajectory is exploited to detect faults during the tracking maneuvers. In order to validate the proposed approach, an extensive experimental test campaign was conducted using the Jaguar V4 Dr.Robot platform.

Kinematics, dynamics, and control of underwater robotic snake based on a rigid-soft unified model

ABSTRACT With the advancement of underwater biomimetic robots, many kinds of underwater snake robots have been developed to perform various marine inspection and maintenance operations. This paper introduces an innovative biomimetic extension to underwater robotic vehicles, an underwater rigid-soft snake robot, which is operated by a combination of rigid propulsion modules and soft joint modules. The essential point is how to jointly mathematically model soft joints and rigid modules with different physical property. The Constant Curvature assumption is widely used in modeling of soft module robots. However, the limitation of this assumption is that it can't accurately describe the deformation of soft robots when performing dynamic tasks. We propose a methodology, rigid-soft unified model, for kinematic and dynamic modeling by viewing soft joint as flexible universal joint. The motion analysis of the robot under the influence of water flow in different postures is completed. Furthermore, we develop a closed loop hierarchical trajectory controller for the snake robot. Especially in the part of dynamic control system, we compare the tracking performance of different controllers.

An intelligent transport system capable of collecting or foraging with many robotic vehicles: An intelligent computing paradigm

Self-driving vehicles are increasingly vital for various environmental tasks, such as data gathering, remote sensing, and mapping. They are particularly important in transportation, where advanced robotic vehicles can operate effectively without human oversight in challenging conditions. One exciting application is using collaborative autonomous robotic vehicles to locate specific points of interest like accidents, congestion, rain, fog, or icy roads. This article explores multi-robot systems for transportation tasks, considering interference that may impact the robot group’s performance. A mathematical model is analysed to quantify the influence of interference and transformed into a dimensionless form for analysis. The system is studied numerically, and a neural soft computing technique, LMA-NN, is proposed. The technique is established on a neural network. For performance evaluation of the LMA-NN technique, different performance benchmarks such as mean square error and absolute error with reference solution are employed. The results are also presented graphically.

Field Oriented Control of Brushless Direct Current Motor for Electric Vehicle Robot Obstacle Detection and Avoidance

This paper presents an approach to implement Field Oriented Control (FOC) brushless directcurrent motor using PID Controller for electric vehicle obstacle detection and avoidance. A state spacemodel of the BLDC motor with FOC was model and simulated using MATLAB/Simulink to validate thestability of the proposed system. The overall system was validated in real time implementation using microcontroller and Ultrasonic Sensor. The detection and recognition of objects, as well as making anautonomous decision to change its trajectory which is based on predetermined threshold distance of 5cmwere analyzed.

Collision-free output-feedback super-twisting control of robotic surface vehicles for coordinated path following with experiments

This paper addresses the coordinated path following (CPF) control of robotic surface vehicles (RSVs) in the presence of multiple obstacles and lumped disturbances over a resource-constrained wireless network. A collision-free output-feedback super-twisting control architecture is proposed for CPF without using velocity measurements. Specifically, robust exact differentiator observers are designed at first to recover the unmeasured velocities, and estimate the lumped disturbances, simultaneously. Next, anti-disturbance output-feedback super-twisting control laws are proposed to achieve individual path following in earth-fixed reference frame, and an adaptive potential field with a user-defined collision hazard degree is introduced to avoid the collisions with obstacles. To reduce the network traffic, self-triggered path updating laws are then designed for avoiding the continuous transmitting and listening of neighboring RSVs. The stability analysis shows that the closed-loop system is input-to-state stable outside the collision avoidance region, and Zeno behavior will not happen. Experiments are finally conducted to validate the efficacy of the proposed collision-free output-feedback super-twisting control method for the self-triggered CPF of RSVs.

Structural analysis of different materials used in ornithopter for better strength and application

An ornithopter is a biomimicry of a flying bird or insect which is power-driven by an electronic powered battery and mechanical components such as a gearbox and spars. These bio-inspired flying robotic vehicles are being inspected and developed for various applications in their field but are currently not at that level to have a successful flight. It is not easy to select a such material for better achievement and performance of an ornithopter which must withstand not only aerodynamically forces applied on it but also damages occur during its performance segments just like as take-off, cruising, different altitude, landing, or any activities enrolled by ornithopter. The core objective of this paper is to provide a material for an ornithopter that gives a better stand respect to applied load i.e., stress and varying strain limit from the initial low to its fracture point with respect to materials like Aluminium alloy, E-glass fibre-honeycomb, Titanium alloy, Carbon fibre etc. A FEA analysis is done to understand these problems and to analyse the various elements to make sure suitable material has been chosen.