Vision based leader-follower formation control for mobile robots

Creating systems with multiple autonomous vehicles places severe demands on the design of control schemes. Robot formation control plays a vital role in coordinating robots. As the number of members in a system rise, the complexity of each member increases. There is a proportional increase in the quantity and complexity of onboard sensing, control and computation. This thesis investigates the control of a group of mobile robots consisting of a leader and several followers to maintain a desired geometric formation --Abstract, page iii

Path planning for mobile robots in the real world: handling multiple objectives, hierarchical structures and partial information

Autonomous robots in real-world environments face a number of challenges even to accomplish apparently simple tasks like moving to a given location. We present four realistic scenarios in which robot navigation takes into account partial information, hierarchical structures, and multiple objectives. We start by discussing navigation in indoor environments shared with people, where routes are characterized by effort, risk, and social impact. Next, we improve navigation by computing optimal trajectories and implementing human-friendly local navigation behaviors. Finally, we move to outdoor environments, where robots rely on uncertain traversability estimations and need to account for the risk of getting stuck or having to change route

Silhouette-Informed Trajectory Generation Through a Wire Maze for Small UAS

Current rapidly-exploring random tree (RRT) algorithms rely on proximity query packages that often include collision checkers, tolerance verification, and distance computation algorithms for the generation of safe paths. In this paper, we broaden the information available to the path-planning algorithm by incorporating silhouette information of nearby obstacles in conflict. A silhouette-informed tree (SIT) is generated through the flight-safe region of a wire maze for a single unmanned aerial system (UAS). The silhouette is used to extract local geometric information of nearby obstacles and provide path alternatives around these obstacles. Thus, focusing the search for the generation of new tree branches near these obstacles, and decreasing the number of samples required to explore the narrow corridors within the wire maze. The SIT is then processed to extract a path that connects the initial location of the UAS with the goal, reduce the number of line segments in this path if possible, and smooth the resulting path using Pythagorean Hodograph Bezier curves. To ensure that the smoothed path remains in the flight-safe region of the configuration space, a tolerance verification algorithm for Bezier curves and convex polytopes in three dimensions is proposed. Lastly, temporal specifications are imposed on the smoothed path in the shape of an arbitrary speed profile

Optimization of an Autonomous Mobile Robot Path Planning Based on Improved Genetic Algorithms

Mobile robots are intended to operate in a variety of environments, and they need to be able to navigate and travel around obstacles, such as objects and barriers. In order to guarantee that the robot will not come into contact with any obstacles or other objects during its movement, algorithms for path planning have been demonstrated. The basic goal while constructing a route is to find the fastest and smoothest route between the starting point and the destination. This article describes route planning using the improvised genetic algorithm with the Bezier Curve (GA-BZ). This study carried out two main experiments, each using a 20x20 random grid map model with varying percentages of obstacles (5%, 15%, and 30% in the first experiment, and 25% and 50% in the second). In the initial experiments, the population (PN), generation (GN), and mutation rate (MR) of genetic algorithms (GA) will be altered to the following values: (PN = 100, 125, 150, or 200; GN = 100, 125, 150; and MR = 0.1, 0.3, 0.5, 0.7) respectively. The goal is to evaluate the effectiveness of AMR in terms of travel distance (m), total time (s), and total cost (RM) in comparison to traditional GA and GA-BZ. The second experiment examined robot performance utilising GA, GA-BZ, Simulated Annealing (SA), A-Star (A*), and Dijkstra's Algorithms (DA) for path distance (m), time travel (s), and fare trip (RM). The simulation results are analysed, compared, and explained. In conclusion, the project is summarised

Human-aware space sharing and navigation for an interactive robot

Les méthodes de planification de mouvements robotiques se sont développées à un rythme accéléré ces dernières années. L'accent a principalement été mis sur le fait de rendre les robots plus efficaces, plus sécurisés et plus rapides à réagir à des situations imprévisibles. En conséquence, nous assistons de plus en plus à l'introduction des robots de service dans notre vie quotidienne, en particulier dans les lieux publics tels que les musées, les centres commerciaux et les aéroports. Tandis qu'un robot de service mobile se déplace dans l'environnement humain, il est important de prendre en compte l'effet de son comportement sur les personnes qu'il croise ou avec lesquelles il interagit. Nous ne les voyons pas comme de simples machines, mais comme des agents sociaux et nous nous attendons à ce qu'ils se comportent de manière similaire à l'homme en suivant les normes sociétales comme des règles. Ceci a créé de nouveaux défis et a ouvert de nouvelles directions de recherche pour concevoir des algorithmes de commande de robot, qui fournissent des comportements de robot acceptables, lisibles et proactifs. Cette thèse propose une méthode coopérative basée sur l'optimisation pour la planification de trajectoire et la navigation du robot avec des contraintes sociales intégrées pour assurer des mouvements de robots prudents, conscients de la présence de l'être humain et prévisibles. La trajectoire du robot est ajustée dynamiquement et continuellement pour satisfaire ces contraintes sociales. Pour ce faire, nous traitons la trajectoire du robot comme une bande élastique (une construction mathématique représentant la trajectoire du robot comme une série de positions et une différence de temps entre ces positions) qui peut être déformée (dans l'espace et dans le temps) par le processus d'optimisation pour respecter les contraintes données. De plus, le robot prédit aussi les trajectoires humaines plausibles dans la même zone d'exploitation en traitant les chemins humains aussi comme des bandes élastiques. Ce système nous permet d'optimiser les trajectoires des robots non seulement pour le moment présent, mais aussi pour l'interaction entière qui se produit lorsque les humains et les robots se croisent les uns les autres. Nous avons réalisé un ensemble d'expériences avec des situations interactives humains-robots qui se produisent dans la vie de tous les jours telles que traverser un couloir, passer par une porte et se croiser sur de grands espaces ouverts. La méthode de planification coopérative proposée se compare favorablement à d'autres schémas de planification de la navigation à la pointe de la technique. Nous avons augmenté le comportement de navigation du robot avec un mouvement synchronisé et réactif de sa tête. Cela permet au robot de regarder où il va et occasionnellement de détourner son regard vers les personnes voisines pour montrer que le robot va éviter toute collision possible avec eux comme prévu par le planificateur. À tout moment, le robot pondère les multiples critères selon le contexte social et décide de ce vers quoi il devrait porter le regard. Grâce à une étude utilisateur en ligne, nous avons montré que ce mécanisme de regard complète efficacement le comportement de navigation ce qui améliore la lisibilité des actions du robot. Enfin, nous avons intégré notre schéma de navigation avec un système de supervision plus large qui peut générer conjointement des comportements du robot standard tel que l'approche d'une personne et l'adaptation de la vitesse du robot selon le groupe de personnes que le robot guide dans des scénarios d'aéroport ou de musée.The methods of robotic movement planning have grown at an accelerated pace in recent years. The emphasis has mainly been on making robots more efficient, safer and react faster to unpredictable situations. As a result we are witnessing more and more service robots introduced in our everyday lives, especially in public places such as museums, shopping malls and airports. While a mobile service robot moves in a human environment, it leaves an innate effect on people about its demeanor. We do not see them as mere machines but as social agents and expect them to behave humanly by following societal norms and rules. This has created new challenges and opened new research avenues for designing robot control algorithms that deliver human-acceptable, legible and proactive robot behaviors. This thesis proposes a optimization-based cooperative method for trajectoryplanning and navigation with in-built social constraints for keeping robot motions safe, human-aware and predictable. The robot trajectory is dynamically and continuously adjusted to satisfy these social constraints. To do so, we treat the robot trajectory as an elastic band (a mathematical construct representing the robot path as a series of poses and time-difference between those poses) which can be deformed (both in space and time) by the optimization process to respect given constraints. Moreover, we also predict plausible human trajectories in the same operating area by treating human paths also as elastic bands. This scheme allows us to optimize the robot trajectories not only for the current moment but for the entire interaction that happens when humans and robot cross each other's paths. We carried out a set of experiments with canonical human-robot interactive situations that happen in our everyday lives such as crossing a hallway, passing through a door and intersecting paths on wide open spaces. The proposed cooperative planning method compares favorably against other stat-of-the-art human-aware navigation planning schemes. We have augmented robot navigation behavior with synchronized and responsive movements of the robot head, making the robot look where it is going and occasionally diverting its gaze towards nearby people to acknowledge that robot will avoid any possible collision with them. At any given moment the robot weighs multiple criteria according to the social context and decides where it should turn its gaze. Through an online user study we have shown that such gazing mechanism effectively complements the navigation behavior and it improves legibility of the robot actions. Finally, we have integrated our navigation scheme with a broader supervision system which can jointly generate normative robot behaviors such as approaching a person and adapting the robot speed according to a group of people who the robot guides in airports or museums

Feasible, Robust and Reliable Automation and Control for Autonomous Systems

The Special Issue book focuses on highlighting current research and developments in the automation and control field for autonomous systems as well as showcasing state-of-the-art control strategy approaches for autonomous platforms. The book is co-edited by distinguished international control system experts currently based in Sweden, the United States of America, and the United Kingdom, with contributions from reputable researchers from China, Austria, France, the United States of America, Poland, and Hungary, among many others. The editors believe the ten articles published within this Special Issue will be highly appealing to control-systems-related researchers in applications typified in the fields of ground, aerial, maritime vehicles, and robotics as well as industrial audiences

On the motion planning & control of nonlinear robotic systems

In the last decades, we saw a soaring interest in autonomous robots boosted not only by academia and industry, but also by the ever in- creasing demand from civil users. As a matter of fact, autonomous robots are fast spreading in all aspects of human life, we can see them clean houses, navigate through city traffic, or harvest fruits and vegetables. Almost all commercial drones already exhibit unprecedented and sophisticated skills which makes them suitable for these applications, such as obstacle avoidance, simultaneous localisation and mapping, path planning, visual-inertial odometry, and object tracking. The major limitations of such robotic platforms lie in the limited payload that can carry, in their costs, and in the limited autonomy due to finite battery capability. For this reason researchers start to develop new algorithms able to run even on resource constrained platforms both in terms of computation capabilities and limited types of endowed sensors, focusing especially on very cheap sensors and hardware. The possibility to use a limited number of sensors allowed to scale a lot the UAVs size, while the implementation of new efficient algorithms, performing the same task in lower time, allows for lower autonomy. However, the developed robots are not mature enough to completely operate autonomously without human supervision due to still too big dimensions (especially for aerial vehicles), which make these platforms unsafe for humans, and the high probability of numerical, and decision, errors that robots may make. In this perspective, this thesis aims to review and improve the current state-of-the-art solutions for autonomous navigation from a purely practical point of view. In particular, we deeply focused on the problems of robot control, trajectory planning, environments exploration, and obstacle avoidance

Path planning and map monitoring for self-driving vehicles based on HD maps

Este trabajo ha sido realizado dentro del contexto del proyecto Techs4AgeCar en el grupo de investigación Robesafe, cuyo objetivo es el desarrollo de un vehículo de conducción autónoma. Forma parte de dos líneas distintas del proyecto, la de mapeado y la de planificación, ya que ambas están directamente relacionadas. Se ha desarrollado un planificador de rutas global basado en mapas de alta defición (HD Maps) offline previamente generados. Por otro lado, también se ha cubierto toda la parte de generación de mapas que posteriormente son utilizados por el planificador. Además, se ha desarrollado un módulo capaz de aprovechar la información proporcionado por el mapa, de forma que se monitorizan los elementos relevantes y cercanos al coche que afectan a la ruta, como son carriles, intersecciones y elementos regulatoriosThis work has been done within the context of the Techs4AgeCar project in the Robesafe research group, whose project focuses on the development of an autonomous driving vehicle. This work is part of two different layers of the project, mapping and planning layers, since both are directly related. A global route planner has been developed based on previously generated offline HD Maps. Therefore, the entire part of generating maps that are later used by the planner has also been covered. In addition, a module capable of taking advantage of the information provided by the map has been developed, so that the relevant elements close to the vehicle that affect the route such as lanes, intersections and regulatory elements are monitored.Máster Universitario en Ingeniería Industrial (M 141

Using a mobile robot for hazardous substances detection in a factory environment

Dupla diplomação com a UTFPR - Universidade Tecnológica Federal do ParanáIndustries that work with toxic materials need extensive security protocols to avoid accidents. Instead of having fixed sensors, the concept of assembling the sensors on a mobile robot that performs the scanning through a defined path is cheaper, configurable and adaptable. This work describes a mobile robot, equipped with several gas sensors and LIDAR, that follows a trajectory based on waypoints, simulating a working Autonomous Guided Vehicle (AGV). At the same time, the robot keeps measuring for toxic gases. In other words, the robot follows the trajectory while the gas concentration is under a defined value. Otherwise, it starts the autonomous leakage search based on a search algorithm that allows to find the leakage position avoiding obstacles in real time. The proposed methodology is verified in simulation based on a model of the real robot. Therefore, three path plannings were developed and their performance compared. A Light Detection And Ranging (LIDAR) device was integrated with the path planning to propose an obstacle avoidance system with a dilation technique to enlarge the obstacles, thus, considering the robot’s dimensions. Moreover, if needed, the robot can be remotely operated with visual feedback. In addition, a controller was made for the robot. Gas sensors were embedded in the robot with Finite Impulse Response (FIR) filter to process the data. A low cost AGV was developed to compete in Festival Nacional de Robótica (Portuguese Robotics Open) 2019 - Gondomar, describing the robot’s control and software solution to the competition.As indústrias que trabalham com materiais tóxicos necessitam de extensos protocolos de segurança para evitar acidentes. Ao invés de ter sensores estáticos, o conceito de instalar sensores em um robô móvel que inspeciona através de um caminho definido é mais barato, configurável e adaptável. O presente trabalho descreve um robô móvel, equipado com vários sensores de gás e LIDAR, que percorre uma trajetória baseada em pontos de controle, simulando um AGV em trabalho. Em simultâneo são efetuadas medidas de gases tóxicos. Em outras palavras, o robô segue uma trajetória enquanto a concentração de gás está abaixo de um valor definido. Caso contrário, inicia uma busca autônoma de vazamento de gás com um algoritmo de busca que permite achar a posição do gás evitando os obstáculos em tempo real. A metodologia proposta é verificada em simulação. Três algoritmos de planejamento de caminho foram desenvolvidos e suas performances comparadas. Um LIDAR foi integrado com o planejamento de caminho para propôr um sistema de evitar obstáculos. Além disso, o robô pode ser operado remotamente com auxílio visual. Foi feito um controlador para o robô. Sensores de gás foram embarcados no robô com um filtro de resposta ao impulso finita para processar as informações. Um veículo guiado automático de baixo custo foi desenvolvido para competir no Festival Nacional de Robótica 2019 - Gondomar. O controle do veículo foi descrito com o programa de solução para a competição