Application of a mobile robot to spatial mapping of radioactive substances in indoor environment

Nuclear medicine requires the use of radioactive substances that can contaminate critical areas (dangerous or hazardous) where the presence of a human must be reduced or avoided. The present work uses a mobile robot in real environment and 3D simulation to develop a method to realize spatial mapping of radioactive substances. The robot should visit all the waypoints arranged in a grid of connectivity that represents the environment. The work presents the methodology to perform the path planning, control and estimation of the robot location. For path planning two methods are approached, one a heuristic method based on observation of problem and another one was carried out an adaptation in the operations of the genetic algorithm. The control of the actuators was based on two methodologies, being the first to follow points and the second to follow trajectories. To locate the real mobile robot, the extended Kalman filter was used to fuse an ultra-wide band sensor with odometry, thus estimating the position and orientation of the mobile agent. The validation of the obtained results occurred using a low cost system with a laser range finder.A medicina nuclear requer o uso de substâncias radioativas que pode vir a contaminar áreas críticas, onde a presença de um ser humano deve ser reduzida ou evitada. O presente trabalho utiliza um robô móvel em ambiente real e em simulação 3D para desenvolver um método para o mapeamento espacial de substâncias radioativas. O robô deve visitar todos os waypoinst dispostos em uma grelha de conectividade que representa o ambiente. O trabalho apresenta a metodologia para realizar o planejamento de rota, controle e estimação da localização do robô. Para o planejamento de rota são abordados dois métodos, um baseado na heurística ao observar o problema e ou outro foi realizado uma adaptação nas operações do algoritmo genético. O controle dos atuadores foi baseado em duas metodologias, sendo a primeira para seguir de pontos e a segunda seguir trajetórias. Para localizar o robô móvel real foi utilizado o filtro de Kalman extendido para a fusão entre um sensor ultra-wide band e odometria, estimando assim a posição e orientação do agente móvel. A validação dos resultados obtidos ocorreu utilizando um sistema de baixo custo com um laser range finder

Mobile Robot Path Following Controller Based On the Sirms Dynamically Connected Fuzzy Inference Model

This paper presents a simple and effective way to implement a path following controller for a differential drive wheeled mobile robot based on the single input rule modules (SIRMs) dynamically connected fuzzy inference model. The control of the mobile robot is divided into two control actions performed in parallel; the heading and the velocity controller. For the heading controller, each input item is assigned with a SIRM and a dynamic importance degree (DID). The velocity controller structure was modified to simplify the design and to fulfill the requirements of the path following method. Here, a common DID is used. The SIRMs and the dynamic importance degrees are designed such that the angular velocity control takes the highest priority over the linear velocity control of the mobile robot. By using the SIRMs and the dynamic importance degrees, the priority orders of the controls are automatically adjusted according to navigation situations. The proposed fuzzy controller has a simple and intuitively understandable structure, and executes the two control actions entirely in parallel. Simulation results show that the proposed fuzzy controller can drive a mobile robot smoothly with a high precision through a series of waypoints to attain its final target in short time

Mobile Robot Path Following Controller Based On the Sirms Dynamically Connected Fuzzy Inference Model

This paper presents a simple and effective way to implement a path following controller for a differential drive wheeled mobile robot based on the single input rule modules (SIRMs) dynamically connected fuzzy inference model. The control of the mobile robot is divided into two control actions performed in parallel; the heading and the velocity controller. For the heading controller, each input item is assigned with a SIRM and a dynamic importance degree (DID). The velocity controller structure was modified to simplify the design and to fulfill the requirements of the path following method. Here, a common DID is used. The SIRMs and the dynamic importance degrees are designed such that the angular velocity control takes the highest priority over the linear velocity control of the mobile robot. By using the SIRMs and the dynamic importance degrees, the priority orders of the controls are automatically adjusted according to navigation situations. The proposed fuzzy controller has a simple and intuitively understandable structure, and executes the two control actions entirely in parallel. Simulation results show that the proposed fuzzy controller can drive a mobile robot smoothly with a high precision through a series of waypoints to attain its final target in short time

A Strategy for Minimizing Parkinsonian Noise from a Joystick Controlled Wheeled Mobile Robot

This thesis investigates movement of an electric wheelchair as a wheeled mobile robot (WMR) with a battery rechargeable through regenerative braking.The WMR has two wheels, each of which can propel or brake. This leads to four modes of operation: propel-propel, brake-brake, propel-brake, and brake-propel. Braking can be either done by a propelling wheel using negative torques or by regenerative braking which also applies a negative torque. The thesis begins with a presentation of the WMR model. Performances Indices (PI) are introduced as metrics for specific driving scenarios. For almost all scenarios, the PI is used in a model predictive control (MPC) strategy for the following set of scenarios with and without noisy measurements on the distance to a wall which simulate a noisy sensor measurement for: -a wall following scenario -a wall cornering scenario -a combined scenario Results of a combined scenario with Parkinsonian noise on distance to the wall measurements and velocity with and withoutthe use of a notch filter are presented and interpreted. Finally Parkinsonian noise is imposed on a joystick wheelchair control scenario with and without the use of a notch filter. The central result of this thesis is to erase the Parkinsonian tremor from the input of the joystick of a electric wheelchair to improve the life quality of disabled users

130 nm low power CMOS analog multiplier

Processing analog signal often involves analog multiplier and the multiplier is part of system on chip (SoC). Designing such system with a low power consumption is crucial nowadays. It is very important to increase the system battery lifetime. The design also must be smaller in size. In order to reduce the power consumption of the multiplier, an architecture that require smaller current must be designed and the approach is to use a design that is able to function at a low voltage supply. This project has designed the analog multiplier with a low power consumption using Silterra 130 nm Complementary Metal Oxide Semiconductor (CMOS) technology. A four quadrant technique is applied in the design. The scaling of transistor will help in reducing the size of the analog multiplier, and the proposed circuit architecture has produced a compact multiplier. Cadence electronic design automation (EDA) Tools is used to design the circuit. The schematic, layout, physical verification and parasitic extraction with post layout simulation are done to verify the multiplier circuit is functioning. The analog multiplier is operated with 1.2 V voltage supply and the power consumption is 98 μW. At 1 V, the power consumption is 32 μW. The total area for the design is 99 μm²

Design of a strategy to obtain safe paths from collaborative robot teamwork

Documento en PDF a color.figuras, tablasThis doctoral thesis was designed and implemented using a strategy of explorer agents and a management and monitoring system to obtain the shortest and safest paths. The strategy was simulated using Matlab R2016 in 10 test environments. The comparisons were made between the results obtained by considering each robot's work and contrasting it with the results obtained by implementing the cooperative-collaborative strategy. For this purpose, were used two path planning algorithms, they are the A* and the Greedy Best First Search (GBFS). Some changes were made to these classic algorithms to improve their performance to guarantee interactions and comparisons between them, transforming them into Incremental Heuristic (IH) algorithms, which gave rise to a couple of agents with new path planners called IH-A* and IH-GBFS. The cooperative strategy was implemented with IH-A* and IH-GBFS algorithms to obtain the shortest paths. The cooperative process was used 300 times in 100 complete tests (3 times in 10 tests in each of 10 environments), which allowed determining that the strategy decreased the original path (without cooperation) in 79% of the cases. In 20.50% of cases, the author identified that the cooperative process, reduced to less than half the original path. The collaborative strategy was implemented to obtain the safer path, using a communications system that allows the interaction among the explorer agents, the test environment, and the management and monitoring system to generate early warnings and compare the risk between paths. In this work, the risk is due to hidden marks found by the explorer agents; for this reason, it is implemented a potential risk function that allows obtaining the path risk estimated. The path risk estimated metric is the one that facilitates the evaluation and comparison of risk between paths to find safer paths. The AWMRs operates using a kinematic model, a controller, a path planner, and sensors that allow them to navigate through the environment gently and safely. Simultaneously with the explorer agents, the administration and monitoring system as a user interface that facilitates the presentation and consolidation of results were implemented. Subsequently, 16 tests were carried out, implementing the complete cooperative-collaborative strategy in four different environments, which had hidden marks. When analyzing the results, it was determined that the Shortest Safest Estimated Path was found in 62.5% of the tests. A WMR and a square test stage were built. In the test scenario, 240 path tracking tests were carried out (the WMR travelled 24 different paths; the WMR travelled each path ten times). The path data were obtained using odometry with encoders onboard the robot and image processing through an external camera. The author apply a tracking error analysis on the WMR path, travelling a circumference of 3.64 m in length. When comparing the path obtained with the WMR kinematic model with the data obtained using image processing, a Mean Absolute Percentage Error (MAPE) of 2,807% was obtained; and with the odometry data, the MAPE was 1,224%. As a general conclusion, this study has numerically identified the relevance of the implementation of the cooperative-collaborative strategy in robotic teamwork to find shortest and safest paths, a strategy applied in test environments that have obstacles and hidden marks. The cooperative-collaborative strategy can be used in different applications that involve displacement in a dangerous place or environment, such as a minefield or a region at risk of spreading COVID-19.Esta tesis doctoral fue diseñada e implementada utilizando una estrategia de agentes exploradores y un sistema de gestión y seguimiento para obtener caminos más cortos y seguros. La estrategia se simuló utilizando Matlab R2016 en 10 entornos de prueba. Las comparaciones se realizaron entre los resultados obtenidos al considerar el trabajo realizado por cada robot y contrastarlo con los resultados obtenidos al implementar la estrategia cooperativa-colaborativa. Para ello, se utilizaron dos algoritmos de planificación de rutas, que son el A* y el Greedy Best First Search (GBFS). Se realizaron algunos cambios a estos algoritmos clásicos para mejorar su rendimiento para garantizar interacciones y comparaciones entre ellos, transformándolos en algoritmos Heurísticos Incrementales (IH), lo que dio lugar a un par de agentes con nuevos planificadores de rutas denominados IH-A * e IH- GBFS. La estrategia cooperativa se implementó con algoritmos IH-A * e IH-GBFS para obtener los caminos más cortos. El proceso cooperativo se utilizó 300 veces en 100 pruebas completas (3 veces en 10 pruebas en cada uno de los 10 entornos), lo que permitió determinar que la estrategia disminuyó la trayectoria original (sin cooperación) en el 79% de los casos. En el 20,50% de los casos, el autor identificó que el proceso cooperativo, redujo la distancia entre inicio y meta a menos de la mitad del recorrido original. La estrategia colaborativa se implementó para obtener el camino más seguro, utilizando un sistema de comunicaciones que permite la interacción entre los agentes exploradores, el entorno de prueba y el sistema de gestión y monitoreo para generar alertas tempranas y comparar el riesgo entre caminos. En este trabajo, el riesgo se debe a las marcas ocultas encontradas por los agentes exploradores; por ello, se implementa una función de riesgo potencial que permite obtener el riesgo de ruta estimado. La métrica estimada de riesgo de ruta es la que facilita la evaluación y comparación de riesgo entre rutas para encontrar rutas más seguras. Los robots autónomos móviles con ruedas (en inglés AWMR) operan utilizando un modelo cinemático, un controlador, un planificador de rutas y sensores que les permiten navegar por el entorno de manera suave y segura. Simultáneamente con los agentes exploradores, el autor implementó un sistema de administración y monitoreo como interfaz de usuario que facilita la presentación y consolidación de resultados. Posteriormente, se realizaron 16 pruebas, implementando la estrategia cooperativa-colaborativa completa en cuatro entornos diferentes, que tenían marcas ocultas. Al analizar los resultados, se determinó que una ruta estimada más corta y más segura se obtenía en el 62.5% de las pruebas. Se construyeron un WMR y un escenario de prueba cuadrado. En el escenario de prueba, se llevaron a cabo 240 pruebas de seguimiento de ruta (el WMR recorrió 24 rutas diferentes; el WMR recorrió cada ruta diez veces). Los datos de la trayectoria se obtuvieron utilizando odometría con encoders a bordo del robot y procesamiento de imágenes a través de una cámara externa. El autor aplica un análisis de error de seguimiento en la ruta recorrida por el WMR, generando una circunferencia de 3,64 m de longitud. Al comparar la ruta obtenida con el modelo cinemático del WMR con los datos obtenidos usando el procesamiento de imágenesse obtuvo un error de porcentaje absoluto medio (MAPE) de 2.807%; y con los datos de odometría, el MAPE fue de 1,224%. Como conclusión general, este estudio ha identificado numéricamente la relevancia de la implementación de la estrategia cooperativa-colaborativa en el trabajo en equipo robótico para encontrar caminos más cortos y seguros, estrategia aplicada en entornos de prueba que poseen obstáculos y marcas ocultas. La estrategia cooperativa-colaborativa puede ser utilizada en diferentes aplicaciones que involucran el desplazamiento en un lugar o entorno peligroso, como pueden ser un campo minado o una región en riesgo de propagación de COVID-19.DoctoradoDoctor en Ingeniería - Ingeniería Automátic

A survey on fractional order control techniques for unmanned aerial and ground vehicles

In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade

Wheeled Mobile Robots: State of the Art Overview and Kinematic Comparison Among Three Omnidirectional Locomotion Strategies

In the last decades, mobile robotics has become a very interesting research topic in the feld of robotics, mainly because of population ageing and the recent pandemic emergency caused by Covid-19. Against this context, the paper presents an overview on wheeled mobile robot (WMR), which have a central role in nowadays scenario. In particular, the paper describes the most commonly adopted locomotion strategies, perception systems, control architectures and navigation approaches. After having analyzed the state of the art, this paper focuses on the kinematics of three omnidirectional platforms: a four mecanum wheels robot (4WD), a three omni wheel platform (3WD) and a two swerve-drive system (2SWD). Through a dimensionless approach, these three platforms are compared to understand how their mobility is afected by the wheel speed limitations that are present in every practical application. This original comparison has not been already presented by the literature and it can be used to improve our understanding of the kinematics of these mobile robots and to guide the selection of the most appropriate locomotion system according to the specifc application

Navigating Discrete Difference Equation Governed WMR by Virtual Linear Leader Guided HMPC

In this paper, we revisit model predictive control (MPC) for the classical wheeled mobile robot (WMR) navigation problem. We prove that the reachable set based hierarchical MPC (HMPC), a state-of-the-art MPC, cannot handle WMR navigation in theory due to the non-existence of non-trivial linear system with an under-approximate reachable set of WMR. Nevertheless, we propose a virtual linear leader guided MPC (VLL-MPC) to enable HMPC structure. Different from current HMPCs, we use a virtual linear system with an under-approximate path set rather than the traditional trace set to guide the WMR. We provide a valid construction of the virtual linear leader. We prove the stability of VLL-MPC, and discuss its complexity. In the experiment, we demonstrate the advantage of VLL-MPC empirically by comparing it with NMPC, LMPC and anytime RRT* in several scenarios