A control architecture and human interface for agile, reconfigurable micro aerial vehicle formations

This thesis considers the problem of controlling a group of micro aerial vehicles for agile maneuvering cooperatively, or distributively. We first introduce the background and motivation for micro aerial vehicles, especially for the popular multi-rotor aerial vehicle platform. Then, we discuss the dynamics of quadrotor helicopters. A quadrotor is a specific kind of multi-rotor aerial vehicle with a special property called differential flatness, which simplifies the algorithm of trajectory planning, such that, instead of planning a trajectory in a 12-dimensional state space and 4-dimensional input space, we only need to plan the trajectory in 4-dimensional, so called, flat output space, while the 12-dimensional state and 4-dimensional input can be recovered from a mapping called endogenous transformation. We propose a series of approaches to achieve agile maneuvering of a dynamic quadrotor formation, from controlling a single quadrotor in an artificial vector field, to controlling a group of quadrotors in a Virtual Rigid Body (VRB) framework, to balancing the effect between the human control and autonomy for collision avoidance, and to fast on-line distributed collision avoidance with Buffered Voronoi Cells (BVC). In the vector field method, we generate velocity, acceleration, jerk and snap fields, depending on the tasks, or the positions of obstacles, such that a single quadrotor can easily find its required state and input from the endogenous transformation in order to track the artificial vector field. Next, with a Virtual Rigid Body framework, we let a group of quadrotors follow a single control command while also keeping a required formation, or even reconfigure from one formation to another. The Virtual Rigid Body framework decouples the trajectory planning problem into two sub-problems. Then we consider the problem of collision avoidance of the quadrotor formation when it is meanwhile tele-operated by a single human operator. The autonomy with collision avoidance algorithm, based on the vector field methods for a single quadrotor, is an assistive portion of the quadrotor formation controller, such that the human operator can focus on his/her high-level tasks, leaving the low-level collision avoidance task be handled automatically. We also consider the full autonomy problem of quadrotor formations when reconfiguring from one formation to another by developing a fast, on-line distributed collision avoidance algorithm using Buffered Voronoi Cells (BVCs). Our BVC based collision avoidance algorithm only requires sensed relative position, rather than relative position and velocity, while the computational complexity is comparable to other methods like velocity obstacles. At last, we introduce our experimental quadrotor platform which is built from PixHawk flight controller and Odroid-XU4 single-board computer. The hardware and software architecture of this multiple-quadrotor platform is described in detail so that our platform can easily be adopted and extended with different purposes. Our conclusion remark and discussion of future work are also given in this thesi

Recent Research in Cooperative Control of Multivehicle Systems

This paper presents a survey of recent research in cooperative control of multivehicle systems, using a common mathematical framework to allow different methods to be described in a unified way. The survey has three primary parts: an overview of current applications of cooperative control, a summary of some of the key technical approaches that have been explored, and a description of some possible future directions for research. Specific technical areas that are discussed include formation control, cooperative tasking, spatiotemporal planning, and consensus

Information Surfing for Radiation Building

We develop a control scheme for a group of mobile sensors to map radiation over a given planar polygonal region. The advantage of this methodology is that it provides quick situational awareness regarding radiation levels, which is being updated and refined in real- time as more measurements become available. The control algorithm is based on the concept of information surfing, where navigation is done by following information gradients, taking into account sensing performance and the dynamics of the observed proces

Multi-Robot Persistent Coverage in Complex Environments

Los recientes avances en robótica móvil y un creciente desarrollo de robots móviles asequibles han impulsado numerosas investigaciones en sistemas multi-robot. La complejidad de estos sistemas reside en el diseño de estrategias de comunicación, coordinación y controlpara llevar a cabo tareas complejas que un único robot no puede realizar. Una tarea particularmente interesante es la cobertura persistente, que pretende mantener cubierto en el tiempo un entorno con un equipo de robots moviles. Este problema tiene muchas aplicaciones como aspiración o limpieza de lugares en los que la suciedad se acumula constantemente, corte de césped o monitorización ambiental. Además, la aparición de vehículos aéreos no tripulados amplía estas aplicaciones con otras como la vigilancia o el rescate.Esta tesis se centra en el problema de cubrir persistentemente entornos progresivamente mas complejos. En primer lugar, proponemos una solución óptima para un entorno convexo con un sistema centralizado, utilizando programación dinámica en un horizonte temporalnito. Posteriormente nos centramos en soluciones distribuidas, que son más robustas, escalables y eficientes. Para solventar la falta de información global, presentamos un algoritmo de estimación distribuido con comunicaciones reducidas. Éste permite a los robots teneruna estimación precisa de la cobertura incluso cuando no intercambian información con todos los miembros del equipo. Usando esta estimación, proponemos dos soluciones diferentes basadas en objetivos de cobertura, que son los puntos del entorno en los que más se puedemejorar dicha cobertura. El primer método es un controlador del movimiento que combina un término de gradiente con un término que dirige a los robots hacia sus objetivos. Este método funciona bien en entornos convexos. Para entornos con algunos obstáculos, el segundométodo planifica trayectorias abiertas hasta los objetivos, que son óptimas en términos de cobertura. Finalmente, para entornos complejos no convexos, presentamos un algoritmo capaz de encontrar particiones equitativas para los robots. En dichas regiones, cada robotplanifica trayectorias de longitud finita a través de un grafo de caminos de tipo barrido.La parte final de la tesis se centra en entornos discretos, en los que únicamente un conjunto finito de puntos debe que ser cubierto. Proponemos una estrategia que reduce la complejidad del problema separándolo en tres subproblemas: planificación de trayectoriascerradas, cálculo de tiempos y acciones de cobertura y generación de un plan de equipo sin colisiones. Estos subproblemas más pequeños se resuelven de manera óptima. Esta solución se utiliza en último lugar para una novedosa aplicación como es el calentamiento por inducción doméstico con inductores móviles. En concreto, la adaptamos a las particularidades de una cocina de inducción y mostramos su buen funcionamiento en un prototipo real.Recent advances in mobile robotics and an increasing development of aordable autonomous mobile robots have motivated an extensive research in multi-robot systems. The complexity of these systems resides in the design of communication, coordination and control strategies to perform complex tasks that a single robot can not. A particularly interesting task is that of persistent coverage, that aims to maintain covered over time a given environment with a team of robotic agents. This problem is of interest in many applications such as vacuuming, cleaning a place where dust is continuously settling, lawn mowing or environmental monitoring. More recently, the apparition of useful unmanned aerial vehicles (UAVs) has encouraged the application of the coverage problem to surveillance and monitoring. This thesis focuses on the problem of persistently covering a continuous environment in increasingly more dicult settings. At rst, we propose a receding-horizon optimal solution for a centralized system in a convex environment using dynamic programming. Then we look for distributed solutions, which are more robust, scalable and ecient. To deal with the lack of global information, we present a communication-eective distributed estimation algorithm that allows the robots to have an accurate estimate of the coverage of the environment even when they can not exchange information with all the members of the team. Using this estimation, we propose two dierent solutions based on coverage goals, which are the points of the environment in which the coverage can be improved the most. The rst method is a motion controller, that combines a gradient term with a term that drives the robots to the goals, and which performs well in convex environments. For environments with some obstacles, the second method plans open paths to the goals that are optimal in terms of coverage. Finally, for complex, non-convex environments we propose a distributed algorithm to nd equitable partitions for the robots, i.e., with an amount of work proportional to their capabilities. To cover this region, each robot plans optimal, nite-horizon paths through a graph of sweep-like paths. The nal part of the thesis is devoted to discrete environment, in which only a nite set of points has to be covered. We propose a divide-and-conquer strategy to separate the problem to reduce its complexity into three smaller subproblem, which can be optimally solved. We rst plan closed paths through the points, then calculate the optimal coverage times and actions to periodically satisfy the coverage required by the points, and nally join together the individual plans of the robots into a collision-free team plan that minimizes simultaneous motions. This solution is eventually used for a novel application that is domestic induction heating with mobile inductors. We adapt it to the particular setting of a domestic hob and demonstrate that it performs really well in a real prototype.<br /

Simultaneous deployment and tracking multi-robot strategies with connectivity maintenance

Multi-robot teams composed of ground and aerial vehicles have gained attention during the last few years. We present a scenario where both types of robots must monitor the same area from different view points. In this paper, we propose two Lloyd-based tracking strategies to allow the ground robots (agents) to follow the aerial ones (targets), keeping the connectivity between the agents. The first strategy establishes density functions on the environment so that the targets acquire more importance than other zones, while the second one iteratively modifies the virtual limits of the working area depending on the positions of the targets. We consider the connectivity maintenance due to the fact that coverage tasks tend to spread the agents as much as possible, which is addressed by restricting their motions so that they keep the links of a minimum spanning tree of the communication graph. We provide a thorough parametric study of the performance of the proposed strategies under several simulated scenarios. In addition, the methods are implemented and tested using realistic robotic simulation environments and real experiments