Autonomous Mobile Robot Motion Control for Hospital Disinfection

As our society develops, robotic systems become indispensable. In producing automation can be used for scanning the impure areas in hospital.  In this article MATLAB's "Robotics System Toolbox," to simulate robot navigation. This essay attempts to demonstrate the efficacy of two path planning techniques: pure-pursuit and the probabilistic roadmap (PRM). To compare the performances of four maps, whose difficulty was gradually increased. For PRM, the number of nodes was first set after the map had been loaded. Initial and final positions were then established. Following that, the program built a possible network of links between the nodes at the start and goal locations. Finally, the algorithm analyzed this network of connected nodes to return a collision-free path. In pure-pursuit, the algorithm's main goal is to select a suitable look-ahead distance. In its most basic form, The Pure Pursuit algorithm examines the difference in heading between the current vehicle and the objective point along the course. It is a proportional controller. The effectiveness of the Pure Pursuit algorithm implementations was tested in a variety of situations. The algorithm used in all of the tests followed a straight path between high level waypoints. It's necessary to keep in mind that PRM path position was the only navigation sensor employed in these studies when analyzing their results

Control of Outdoor Robots at Higher Speeds on Challenging Terrain

This thesis studies the motion control of wheeled mobile robots. Its focus is set on high speed control on challenging terrain. Additionally, it deals with the general problem of path following, as well as path planning and obstacle avoidance in difficult conditions. First, it proposes a heuristic longitudinal control for any wheeled mobile robot, and evaluates it on different kinematic configurations and in different conditions, including laboratory experiments and participation in a robotic competition. Being the focus of the thesis, high speed control on uneven terrain is thoroughly studied, and a novel control law is proposed, based on a new model representation of skid-steered vehicles, and comprising of nonlinear lateral and longitudinal control. The lateral control part is based on the Lyapunov theory, and the convergence of the vehicle to the geometric reference path is proven. The longitudinal control is designed for high speeds, taking actuator saturation and the vehicle properties into account. The complete solution is experimentally tested on two different vehicles on several different terrain types, reaching the speeds of ca. 6 m/s, and compared against two state-of-the-art algorithms. Furthermore, a novel path planning and obstacle avoidance system is proposed, together with an extension of the proposed high speed control, which builds up a navigation system capable of autonomous outdoor person following. This system is experimentally compared against two classical obstacle avoidance methods, and evaluated by following a human jogger in outdoor environments, with both static and dynamic obstacles. All the proposed methods, together with various different state-of-the-art control approaches, are unified into one framework. The proposed framework can be used to control any wheeled mobile robot, both indoors and outdoors, at low or high speeds, avoiding all the obstacles on the way. The entire work is released as open-source software

Efficient mobile robot path planning by Voronoi-based heuristic

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Mobile Robots Navigation

Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described

Safe navigation and motion coordination control strategies for unmanned aerial vehicles

Unmanned aerial vehicles (UAVs) have become very popular for many military and civilian applications including in agriculture, construction, mining, environmental monitoring, etc. A desirable feature for UAVs is the ability to navigate and perform tasks autonomously with least human interaction. This is a very challenging problem due to several factors such as the high complexity of UAV applications, operation in harsh environments, limited payload and onboard computing power and highly nonlinear dynamics. Therefore, more research is still needed towards developing advanced reliable control strategies for UAVs to enable safe navigation in unknown and dynamic environments. This problem is even more challenging for multi-UAV systems where it is more efficient to utilize information shared among the networked vehicles. Therefore, the work presented in this thesis contributes towards the state-of-the-art in UAV control for safe autonomous navigation and motion coordination of multi-UAV systems. The first part of this thesis deals with single-UAV systems. Initially, a hybrid navigation framework is developed for autonomous mobile robots using a general 2D nonholonomic unicycle model that can be applied to different types of UAVs, ground vehicles and underwater vehicles considering only lateral motion. Then, the more complex problem of three-dimensional (3D) collision-free navigation in unknown/dynamic environments is addressed. To that end, advanced 3D reactive control strategies are developed adopting the sense-and-avoid paradigm to produce quick reactions around obstacles. A special case of navigation in 3D unknown confined environments (i.e. tunnel-like) is also addressed. General 3D kinematic models are considered in the design which makes these methods applicable to different UAV types in addition to underwater vehicles. Moreover, different implementation methods for these strategies with quadrotor-type UAVs are also investigated considering UAV dynamics in the control design. Practical experiments and simulations were carried out to analyze the performance of the developed methods. The second part of this thesis addresses safe navigation for multi-UAV systems. Distributed motion coordination methods of multi-UAV systems for flocking and 3D area coverage are developed. These methods offer good computational cost for large-scale systems. Simulations were performed to verify the performance of these methods considering systems with different sizes

Motion planning for constrained mobile robots in unknown environments

Ph.DDOCTOR OF PHILOSOPH

Detección de obstáculos estáticos y dinámicos y evitación de colisiones para un vehículo a escala

El objetivo del presente trabajo es el desarrollo e implementación de un software en un vehículo a escala, que permita, mediante un control activo del mismo, realizar una evitación de obstáculos estáticos y/o dinámicos además de un control activo de colisiones. Todo esto, se desarrollará en ROS (Robot Operating System), verificando el diseño en el simulador Gazebo. Antes de plantear la solución al trabajo, se realizará un estudio del estado del arte que permita conocer a fondo los tipos de conducción autónoma reconocidas actualmente, así como una breve descripción de las herramientas a utilizar y del propio vehículo con el que se realizará el ensayo

Sensor Network Based Collision-Free Navigation and Map Building for Mobile Robots

Safe robot navigation is a fundamental research field for autonomous robots including ground mobile robots and flying robots. The primary objective of a safe robot navigation algorithm is to guide an autonomous robot from its initial position to a target or along a desired path with obstacle avoidance. With the development of information technology and sensor technology, the implementations combining robotics with sensor network are focused on in the recent researches. One of the relevant implementations is the sensor network based robot navigation. Moreover, another important navigation problem of robotics is safe area search and map building. In this report, a global collision-free path planning algorithm for ground mobile robots in dynamic environments is presented firstly. Considering the advantages of sensor network, the presented path planning algorithm is developed to a sensor network based navigation algorithm for ground mobile robots. The 2D range finder sensor network is used in the presented method to detect static and dynamic obstacles. The sensor network can guide each ground mobile robot in the detected safe area to the target. Furthermore, the presented navigation algorithm is extended into 3D environments. With the measurements of the sensor network, any flying robot in the workspace is navigated by the presented algorithm from the initial position to the target. Moreover, in this report, another navigation problem, safe area search and map building for ground mobile robot, is studied and two algorithms are presented. In the first presented method, we consider a ground mobile robot equipped with a 2D range finder sensor searching a bounded 2D area without any collision and building a complete 2D map of the area. Furthermore, the first presented map building algorithm is extended to another algorithm for 3D map building

Advanced Mobile Robotics: Volume 3

Mobile robotics is a challenging field with great potential. It covers disciplines including electrical engineering, mechanical engineering, computer science, cognitive science, and social science. It is essential to the design of automated robots, in combination with artificial intelligence, vision, and sensor technologies. Mobile robots are widely used for surveillance, guidance, transportation and entertainment tasks, as well as medical applications. This Special Issue intends to concentrate on recent developments concerning mobile robots and the research surrounding them to enhance studies on the fundamental problems observed in the robots. Various multidisciplinary approaches and integrative contributions including navigation, learning and adaptation, networked system, biologically inspired robots and cognitive methods are welcome contributions to this Special Issue, both from a research and an application perspective