A reliability-based particle filter for humanoid robot self-localization in Robocup Standard Platform League

This paper deals with the problem of humanoid robot localization and proposes a new method for position estimation that has been developed for the RoboCup Standard Platform League environment. Firstly, a complete vision system has been implemented in the Nao robot platform that enables the detection of relevant field markers. The detection of field markers provides some estimation of distances for the current robot position. To reduce errors in these distance measurements, extrinsic and intrinsic camera calibration procedures have been developed and described. To validate the localization algorithm, experiments covering many of the typical situations that arise during RoboCup games have been developed: ranging from degradation in position estimation to total loss of position (due to falls, ‘kidnapped robot’, or penalization). The self-localization method developed is based on the classical particle filter algorithm. The main contribution of this work is a new particle selection strategy. Our approach reduces the CPU computing time required for each iteration and so eases the limited resource availability problem that is common in robot platforms such as Nao. The experimental results show the quality of the new algorithm in terms of localization and CPU time consumption.This work has been supported by the Spanish Science and Innovation Ministry (MICINN) under the CICYT project COBAMI: DPI2011-28507-C02-01/02. The responsibility for the content remains with the authors.Munera Sánchez, E.; Muñoz Alcobendas, M.; Blanes Noguera, F.; Benet Gilabert, G.; Simó Ten, JE. (2013). A reliability-based particle filter for humanoid robot self-localization in Robocup Standard Platform League. Sensors. 13(11):14954-14983. https://doi.org/10.3390/s131114954S1495414983131

Perceção e arquitectura de software para robótica móvel

Doutoramento em Ciências da ComputaçãoWhen developing software for autonomous mobile robots, one has to inevitably tackle some kind of perception. Moreover, when dealing with agents that possess some level of reasoning for executing their actions, there is the need to model the environment and the robot internal state in a way that it represents the scenario in which the robot operates. Inserted in the ATRI group, part of the IEETA research unit at Aveiro University, this work uses two of the projects of the group as test bed, particularly in the scenario of robotic soccer with real robots. With the main objective of developing algorithms for sensor and information fusion that could be used e ectively on these teams, several state of the art approaches were studied, implemented and adapted to each of the robot types. Within the MSL RoboCup team CAMBADA, the main focus was the perception of ball and obstacles, with the creation of models capable of providing extended information so that the reasoning of the robot can be ever more e ective. To achieve it, several methodologies were analyzed, implemented, compared and improved. Concerning the ball, an analysis of ltering methodologies for stabilization of its position and estimation of its velocity was performed. Also, with the goal keeper in mind, work has been done to provide it with information of aerial balls. As for obstacles, a new de nition of the way they are perceived by the vision and the type of information provided was created, as well as a methodology for identifying which of the obstacles are team mates. Also, a tracking algorithm was developed, which ultimately assigned each of the obstacles a unique identi er. Associated with the improvement of the obstacles perception, a new algorithm of estimating reactive obstacle avoidance was created. In the context of the SPL RoboCup team Portuguese Team, besides the inevitable adaptation of many of the algorithms already developed for sensor and information fusion and considering that it was recently created, the objective was to create a sustainable software architecture that could be the base for future modular development. The software architecture created is based on a series of di erent processes and the means of communication among them. All processes were created or adapted for the new architecture and a base set of roles and behaviors was de ned during this work to achieve a base functional framework. In terms of perception, the main focus was to de ne a projection model and camera pose extraction that could provide information in metric coordinates. The second main objective was to adapt the CAMBADA localization algorithm to work on the NAO robots, considering all the limitations it presents when comparing to the MSL team, especially in terms of computational resources. A set of support tools were developed or improved in order to support the test and development in both teams. In general, the work developed during this thesis improved the performance of the teams during play and also the e ectiveness of the developers team when in development and test phases.Durante o desenvolvimento de software para robôs autónomos móveis, e inevitavelmente necessário lidar com algum tipo de perceção. Al em disso, ao lidar com agentes que possuem algum tipo de raciocínio para executar as suas ações, há a necessidade de modelar o ambiente e o estado interno do robô de forma a representar o cenário onde o robô opera. Inserido no grupo ATRI, integrado na unidade de investigação IEETA da Universidade de Aveiro, este trabalho usa dois dos projetos do grupo como plataformas de teste, particularmente no cenário de futebol robótico com robôs reais. Com o principal objetivo de desenvolver algoritmos para fusão sensorial e de informação que possam ser usados eficazmente nestas equipas, v arias abordagens de estado da arte foram estudadas, implementadas e adaptadas para cada tipo de robôs. No âmbito da equipa de RoboCup MSL, CAMBADA, o principal foco foi a perceção da bola e obstáculos, com a criação de modelos capazes de providenciar informação estendida para que o raciocino do robô possa ser cada vez mais eficaz. Para o alcançar, v arias metodologias foram analisadas, implementadas, comparadas e melhoradas. Em relação a bola, foi efetuada uma análise de metodologias de filtragem para estabilização da sua posição e estimação da sua velocidade. Tendo o guarda-redes em mente, foi também realizado trabalho para providenciar informação de bolas no ar. Quanto aos obstáculos, foi criada uma nova definição para a forma como são detetados pela visão e para o tipo de informação fornecida, bem como uma metodologia para identificar quais dos obstáculos são colegas de equipa. Além disso foi desenvolvido um algoritmo de rastreamento que, no final, atribui um identicador único a cada obstáculo. Associado a melhoria na perceção dos obstáculos foi criado um novo algoritmo para realizar desvio reativo de obstáculos. No contexto da equipa de RoboCup SPL, Portuguese Team, al em da inevitável adaptação de vários dos algoritmos j a desenvolvidos para fusão sensorial e de informação, tendo em conta que foi recentemente criada, o objetivo foi criar uma arquitetura sustentável de software que possa ser a base para futuro desenvolvimento modular. A arquitetura de software criada e baseada numa série de processos diferentes e métodos de comunicação entre eles. Todos os processos foram criados ou adaptados para a nova arquitetura e um conjunto base de papeis e comportamentos foi definido para obter uma framework funcional base. Em termos de perceção, o principal foco foi a definição de um modelo de projeção e extração de pose da câmara que consiga providenciar informação em coordenadas métricas. O segundo objetivo principal era adaptar o algoritmo de localização da CAMBADA para funcionar nos robôs NAO, considerando todas as limitações apresentadas quando comparando com a equipa MSL, principalmente em termos de recursos computacionais. Um conjunto de ferramentas de suporte foram desenvolvidas ou melhoradas para auxiliar o teste e desenvolvimento em ambas as equipas. Em geral, o trabalho desenvolvido durante esta tese melhorou o desempenho da equipas durante os jogos e também a eficácia da equipa de programação durante as fases de desenvolvimento e teste

Scaled Autonomy for Networked Humanoids

Humanoid robots have been developed with the intention of aiding in environments designed for humans. As such, the control of humanoid morphology and effectiveness of human robot interaction form the two principal research issues for deploying these robots in the real world. In this thesis work, the issue of humanoid control is coupled with human robot interaction under the framework of scaled autonomy, where the human and robot exchange levels of control depending on the environment and task at hand. This scaled autonomy is approached with control algorithms for reactive stabilization of human commands and planned trajectories that encode semantically meaningful motion preferences in a sequential convex optimization framework. The control and planning algorithms have been extensively tested in the field for robustness and system verification. The RoboCup competition provides a benchmark competition for autonomous agents that are trained with a human supervisor. The kid-sized and adult-sized humanoid robots coordinate over a noisy network in a known environment with adversarial opponents, and the software and routines in this work allowed for five consecutive championships. Furthermore, the motion planning and user interfaces developed in the work have been tested in the noisy network of the DARPA Robotics Challenge (DRC) Trials and Finals in an unknown environment. Overall, the ability to extend simplified locomotion models to aid in semi-autonomous manipulation allows untrained humans to operate complex, high dimensional robots. This represents another step in the path to deploying humanoids in the real world, based on the low dimensional motion abstractions and proven performance in real world tasks like RoboCup and the DRC

Learning Motion Skills for a Humanoid Robot

This thesis investigates the learning of motion skills for humanoid robots. As groundwork, a humanoid robot with integrated fall management was developed as an experimental platform. Then, two different approaches for creating motion skills were investigated. First, one that is based on Cartesian quintic splines with optimized parameters. Second, a reinforcement learning-based approach that utilizes the first approach as a reference motion to guide the learning. Both approaches were tested on the developed robot and on further simulated robots to show their generalization. A special focus was set on the locomotion skill, but a standing-up and kick skill are also discussed. Diese Dissertation beschäftigt sich mit dem Lernen von Bewegungsfähigkeiten für humanoide Roboter. Als Grundlage wurde zunächst ein humanoider Roboter mit integriertem Fall Management entwickelt, welcher als Experimentalplatform dient. Dann wurden zwei verschiedene Ansätze für die Erstellung von Bewegungsfähigkeiten untersucht. Zu erst einer der kartesische quintische Splines mit optimierten Parametern nutzt. Danach wurde ein Ansatz basierend auf bestärkendem Lernen untersucht, welcher den ersten Ansatz als Referenzbewegung benutzt. Beide Ansätze wurden sowohl auf der entwickelten Roboterplatform, als auch auf weiteren simulierten Robotern getestet um die Generalisierbarkeit zu zeigen. Ein besonderer Fokus wurde auf die Fähigkeit des Gehens gelegt, aber auch Aufsteh- und Schussfähigkeiten werden diskutiert

MISSION-ORIENTED HETEROGENEOUS ROBOT COOPERATION BASED ON SMART RESOURCES EXECUTION

Home environments are changing as more technological devices are used to improve daily life. The growing demand for high technology in our homes means that robot integration will soon arrive. Home devices are evolving in a connected paradigm in which data flows to perform efficient home task management. Heterogeneous home robots connected in a network can establish a workflow that complements their capabilities and so increases performance within a mission execution. This work addresses the definition and requirements of a robot-group mission in the home context. The proposed solution relies on a network of smart resources, which are defined as cyber-physical systems that provide high-level service execution. Firstly, control middleware architecture is introduced as the execution base for the Smart resources. Next, the Smart resource topology and its integration within a robotic platform are addressed. Services supplied by Smart resources manage their execution through a robot behavior architecture. Robot behavior execution is hierarchically organized through a mission definition that can be established as an individual or collective approach. Environment model and interaction tasks characterize the operation capabilities of each robot within a mission. Mission goal achievement in a heterogeneous group is enhanced through the complement of the interaction capabilities of each robot. To offer a clearer explanation, a full use case is presented in which two robots cooperate to execute a mission and the previously detailed steps are evaluated. Finally, some of the obtained results are discussed as conclusions and future works is introduced.Los entornos domésticos se encuentran sometidos a un proceso de cambio gracias al empleo de dispositivos tecnológicos que mejoran la calidad de vida de las personas. La creciente demanda de alta tecnología en los hogares señala una próxima incorporación de la robótica de servicio. Los dispositivos domésticos están evolucionando hacia un paradigma de conexión en el cual la información fluye para ofrecer una gestión más eficiente. En este entorno, robots heterogéneos conectados a la red pueden establecer un flujo de trabajo que ofreciendo nuevas soluciones y incrementando la eficiencia en la ejecución de tareas. Este trabajo aborda la definición y los requisitos necesarios para la ejecución de misiones en grupos de robots heterogéneos en entornos domésticos. La solución propuesta se apoya en una red de Smart resources, que son definidos como sistemas ciber-físicos que proporcionan servicios de alto nivel. En primer lugar, se presenta la arquitectura del middleware de control en la cual se basa la ejecución de los Smart resources. A continuación se detalla la topología de los Smart resources, así como su integración en plataformas robóticas. Los servicios proporcionados por los Smart resources gestionan su ejecución mediante una arquitectura de comportamientos para robots. La ejecución de estos comportamientos se organiza de forma jerárquica mediante la definición de una misión con un objetivo establecido de forma individual o colectiva a un grupo de robots. Dentro de una misión, las tareas de modelado e interacción con el entorno define las capacidades de operación de los robots dentro de una misión. Mediante la integración de un grupo heterogéneo de robots sus diversas capacidades son complementadas para el logro un objetivo común. A fin de caracterizar esta propuesta, los mecanismos presentados en este documento se evaluarán en detalle a lo largo de una serie experimentos en los cuales un grupo de robots heterogéneos ejecutan una misión colaborativa para alcanzar un objetivo común. Finalmente, los resultados serán discutidos a modo de conclusiones dando lugar el establecimiento de un trabajo futuro.Els entorns domèstics es troben sotmesos a un procés de canvi gràcies a l'ocupació de dispositius tecnològics que milloren la qualitat de vida de les persones. La creixent demanda d'alta tecnologia a les llars assenyala una propera incorporació de la robòtica de servei. Els dispositius domèstics estan evolucionant cap a un paradigma de connexió en el qual la informació flueix per oferir una gestió més eficient. En aquest entorn, robots heterogenis connectats a la xarxa poden establir un flux de treball que ofereix noves solucions i incrementant l'eficiència en l'execució de tasques. Aquest treball aborda la definició i els requisits necessaris per a l'execució de missions en grups de robots heterogenis en entorns domèstics. La solució proposada es recolza en una xarxa de Smart resources, que són definits com a sistemes ciber-físics que proporcionen serveis d'alt nivell. En primer lloc, es presenta l'arquitectura del middleware de control en la qual es basa l'execució dels Smart resources. A continuació es detalla la tipologia dels Smart resources, així com la seva integració en plataformes robòtiques. Els serveis proporcionats pels Smart resources gestionen la seva execució mitjançant una arquitectura de comportaments per a robots. L'execució d'aquests comportaments s'organitza de forma jeràrquica mitjançant la definició d'una missió amb un objectiu establert de forma individual o col·lectiva a un grup de robots. Dins d'una missió, les tasques de modelatge i interacció amb l'entorn defineix les capacitats d'operació dels robots dins d'una missió. Mitjançant la integració d'un grup heterogeni de robots seves diverses capacitats són complementades per a l'assoliment un objectiu comú. Per tal de caracteritzar aquesta proposta, els mecanismes presentats en aquest document s'avaluaran en detall mitjançant d'una sèrie experiments en els quals un grup de robots heterogenis executen una missió col·laborativa per aconseguir un objectiu comú. Finalment, els resultats seran discutits a manera de conclusions donant lloc a l'establiment d'un treball futur.Munera Sánchez, E. (2017). MISSION-ORIENTED HETEROGENEOUS ROBOT COOPERATION BASED ON SMART RESOURCES EXECUTION [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/88404TESI

Holonomic control and behaviours for the CAMBADA robotic soccer team

Mestrado em Engenharia de Computadores e TelemáticaCAMBADA é a equipa de futebol robótico da liga de tamanho médio do RoboCup criada por investigadores do grupo ATRI do IEETA da Universidade de Aveiro. Esta dissertação apresenta as contribuições desenvolvidas no controlo do movimento holonómico e comportamentos de alto-nível. Ao nível do controlo do movimento, várias restrições que afectam o movimento holonómico foram tratadas. Isto é de vital importância visto que dado o ambiente altamente dinâmico de um jogo de futebol é crucial mover e posicionar os robots eficazmente no campo. Ao nivel dos comportamentos, dada a importância da bola no jogo de futebol, e considerando o trabalho realizado no que diz respeito à estimativa da velocidade da bola, o comportamento de intercepção activa foi desenvolvido permitindo aos robots apanhar a bola prevendo o seu movimento em vez de se moverem directamente para a ela considerando-a estática. Dada a autonomia completa dos robots, a sua percepção do mundo deve ser o mais próxima possivel da realidade. De modo a fornecer, ao robot, informação adicional respeitante ao estado do jogo, um método para determinar se está preso foi desenvolvido. O trabalho implementado melhorou a performance da equipa e contribuiu para vitória de um campeonato nacional, Robótica’09, e a um notável terceiro lugar no RoboCup’09 em Graz, ´Austria. ABSTRACT: CAMBADA is the RoboCup Middle Size League robotic soccer team created by researchers of the ATRI group of IEETA of University of Aveiro. This thesis presents the developed contributions in holonomic motion control and high-level behaviours. At the motion control level, several restrictions affecting holonomic motion were addressed. This is of vital importance since that given the highly dynamic environment of a soccer game it is crucial to move and position the robots efficiently in the field. At the behaviours level, given the importance of the ball in the soccer game, and considering previous work regarding the estimation of the ball velocity, the active interception behaviour was implemented allowing the robots to engage the ball predicting its movement rather than moving directly to it considering it static. Given the full autonomy of the robots, their perception of the game should be as close to reality as possible. In order to supply additional information to the robot regarding the state of the game, a method to detect if it is stuck was developed. The implemented work improved the team performance and contributed to the victory of a National Championship (Robótica’09) and a remarkable third-place in the RoboCup 2009 in Graz, Austria

World Modeling for Intelligent Autonomous Systems

The functioning of intelligent autonomous systems requires constant situation awareness and cognition analysis. Thus, it needs a memory structure that contains a description of the surrounding environment (world model) and serves as a central information hub. This book presents a row of theoretical and experimental results in the field of world modeling. This includes areas of dynamic and prior knowledge modeling, information fusion, management and qualitative/quantitative information analysis

Proceedings of the 9th Conference on Autonomous Robot Systems and Competitions

Welcome to ROBOTICA 2009. This is the 9th edition of the conference on Autonomous Robot Systems and Competitions, the third time with IEEE‐Robotics and Automation Society Technical Co‐Sponsorship. Previous editions were held since 2001 in Guimarães, Aveiro, Porto, Lisboa, Coimbra and Algarve. ROBOTICA 2009 is held on the 7th May, 2009, in Castelo Branco , Portugal. ROBOTICA has received 32 paper submissions, from 10 countries, in South America, Asia and Europe. To evaluate each submission, three reviews by paper were performed by the international program committee. 23 papers were published in the proceedings and presented at the conference. Of these, 14 papers were selected for oral presentation and 9 papers were selected for poster presentation. The global acceptance ratio was 72%. After the conference, eighth papers will be published in the Portuguese journal Robótica, and the best student paper will be published in IEEE Multidisciplinary Engineering Education Magazine. Three prizes will be awarded in the conference for: the best conference paper, the best student paper and the best presentation. The last two, sponsored by the IEEE Education Society ‐ Student Activities Committee. We would like to express our thanks to all participants. First of all to the authors, whose quality work is the essence of this conference. Next, to all the members of the international program committee and reviewers, who helped us with their expertise and valuable time. We would also like to deeply thank the invited speaker, Jean Paul Laumond, LAAS‐CNRS France, for their excellent contribution in the field of humanoid robots. Finally, a word of appreciation for the hard work of the secretariat and volunteers. Our deep gratitude goes to the Scientific Organisations that kindly agreed to sponsor the Conference, and made it come true. We look forward to seeing more results of R&D work on Robotics at ROBOTICA 2010, somewhere in Portugal

Multi-robot behaviors with bearing-only sensors and scale-free coordinates

This thesis presents a low-cost multi-robot system for large populations of robots, a new coordinate system for the robot based on angles between robots and a series of experiments validating robot performance. The new robot platform, the r-one will serve as an educational, outreach and research platform for robotics. I consider the robot's bearing-only sensor model, where each robot is capable of measuring the bearing, but not the distance, to each of its neighbors. This work also includes behaviors demonstrating the efficiency of this approach with this bearing-only sensor model. The new local coordinate systems based on angular information is introduced as scale-free coordinate system . Each robot produces its own local scale-free coordinates to determine the relative positions of its neighbors up to an unknown scaling factor. The computation of scale-free coordinates is analyzed with hardware and simulation validation. For hardware, the scale-free algorithm is tailored to low-cost systems with limited communication bandwidth and sensor resolution. The algorithm also uses a noise sensitivity model to reduce the impact of noise on the computed scale-free coordinates. I validate the algorithm with static and dynamic motion experiments

Planning and Navigation in Dynamic Environments for Mobile Robots and Micro Aerial Vehicles

Reliable and robust navigation planning and obstacle avoidance is key for the autonomous operation of mobile robots. In contrast to stationary industrial robots that often operate in controlled spaces, planning for mobile robots has to take changing environments and uncertainties into account during plan execution. In this thesis, planning and obstacle avoidance techniques are proposed for a variety of ground and aerial robots. Common to most of the presented approaches is the exploitation of the nature of the underlying problem to achieve short planning times by using multiresolution or hierarchical approaches. Short planning times allow for continuous and fast replanning to take the uncertainty in the environment and robot motion execution into account. The proposed approaches are evaluated in simulation and real-world experiments. The first part of this thesis addresses planning for mobile ground robots. One contribution is an approach to grasp and object removal planning to pick objects from a transport box with a mobile manipulation robot. In a multistage process, infeasible grasps are pruned in offline and online processing steps. Collision-free endeffector trajectories are planned to the remaining grasps until a valid removal trajectory can be found. An object-centric local multiresolution representation accelerates trajectory planning. The mobile manipulation components are evaluated in an integrated mobile bin-picking system. Local multiresolution planning is employed for path planning for humanoid soccer robots as well. The used Nao robot is equipped with only relatively low computing power. A resource-efficient path planner including the anticipated movements of opponents on the field is developed as part of this thesis. In soccer games an important subproblem is to reach a position behind the ball to dribble or kick it towards the goal. By the assumption that the opponents have the same intention, an explicit representation of their movements is possible. This leads to paths that facilitate the robot to reach its target position with a higher probability without being disturbed by the other robot. The evaluation for the planner is performed in a physics-based soccer simulation. The second part of this thesis covers planning and obstacle avoidance for micro aerial vehicles (MAVs), in particular multirotors. To reduce the planning complexity, the planning problem is split into a hierarchy of planners running on different levels of abstraction, i.e., from abstract to detailed environment descriptions and from coarse to fine plans. A complete planning hierarchy for MAVs is presented, from mission planners for multiple application domains to low-level obstacle avoidance. Missions planned on the top layer are executed by means of coupled allocentric and egocentric path planning. Planning is accelerated by global and local multiresolution representations. The planners can take multiple objectives into account in addition to obstacle costs and path length, e.g., sensor constraints. The path planners are supplemented by trajectory optimization to achieve dynamically feasible trajectories that can be executed by the underlying controller at higher velocities. With the initialization techniques presented in this thesis, the convergence of the optimization problem is expedited. Furthermore, frequent reoptimization of the initial trajectory allows for the reaction to changes in the environment without planning and optimizing a complete new trajectory. Fast, reactive obstacle avoidance based on artificial potential fields acts as a safety layer in the presented hierarchy. The obstacle avoidance layer employs egocentric sensor data and can operate at the data acquisition frequency of up to 40 Hz. It can slow-down and stop the MAVs in front of obstacles as well as avoid approaching dynamic obstacles. We evaluate our planning and navigation hierarchy in simulation and with a variety of MAVs in real-world applications, especially outdoor mapping missions, chimney and building inspection, and automated stocktaking.Planung und Navigation in dynamischen Umgebungen für mobile Roboter und Multikopter Zuverlässige und sichere Navigationsplanung und Hindernisvermeidung ist ein wichtiger Baustein für den autonomen Einsatz mobiler Roboter. Im Gegensatz zu klassischen Industrierobotern, die in der Regel in abgetrennten, kontrollierten Bereichen betrieben werden, ist es in der mobilen Robotik unerlässlich, Änderungen in der Umgebung und die Unsicherheit bei der Aktionsausführung zu berücksichtigen. Im Rahmen dieser Dissertation werden Verfahren zur Planung und Hindernisvermeidung für eine Reihe unterschiedlicher Boden- und Flugroboter entwickelt und vorgestellt. Den meisten beschriebenen Ansätzen ist gemein, dass die Struktur der zu lösenden Probleme ausgenutzt wird, um Planungsprozesse zu beschleunigen. Häufig ist es möglich, mit abnehmender Genauigkeit zu planen desto weiter eine Aktion in der Zeit oder im Ort entfernt ist. Dieser Ansatz wird lokale Multiresolution genannt. In anderen Fällen ist eine Zerlegung des Problems in Schichten unterschiedlicher Genauigkeit möglich. Die damit zu erreichende Beschleunigung der Planung ermöglicht ein häufiges Neuplanen und somit die Reaktion auf Änderungen in der Umgebung und Abweichungen bei den ausgeführten Aktionen. Zur Evaluation der vorgestellten Ansätze werden Experimente sowohl in der Simulation als auch mit Robotern durchgeführt. Der erste Teil dieser Dissertation behandelt Planungsmethoden für mobile Bodenroboter. Um Objekte mit einem mobilen Roboter aus einer Transportkiste zu greifen und zur Weiterverarbeitung zu einem Arbeitsplatz zu liefern, wurde ein System zur Planung möglicher Greifposen und hindernisfreier Endeffektorbahnen entwickelt. In einem mehrstufigen Prozess werden mögliche Griffe an bekannten Objekten erst in mehreren Vorverarbeitungsschritten (offline) und anschließend, passend zu den erfassten Objekten, online identifiziert. Zu den verbleibenden möglichen Griffen werden Endeffektorbahnen geplant und, bei Erfolg, ausgeführt. Die Greif- und Bahnplanung wird durch eine objektzentrische lokale Multiresolutionskarte beschleunigt. Die Einzelkomponenten werden in einem prototypischen Gesamtsystem evaluiert. Eine weitere Anwendung für die lokale Multiresolutionsplanung ist die Pfadplanung für humanoide Fußballroboter. Zum Einsatz kommen Nao-Roboter, die nur über eine sehr eingeschränkte Rechenleistung verfügen. Durch die Reduktion der Planungskomplexität mit Hilfe der lokalen Multiresolution, wurde die Entwicklung eines Planers ermöglicht, der zusätzlich zur aktuellen Hindernisfreiheit die Bewegung der Gegenspieler auf dem Feld berücksichtigt. Hierbei liegt der Fokus auf einem wichtigen Teilproblem, dem Erreichen einer guten Schussposition hinter dem Ball. Die Tatsache, dass die Gegenspieler vergleichbare Ziele verfolgen, ermöglicht es, Annahmen über mögliche Laufwege zu treffen. Dadurch ist die Planung von Pfaden möglich, die das Risiko, durch einen Gegenspieler passiv geblockt zu werden, reduzieren, so dass die Schussposition schneller erreicht wird. Dieser Teil der Arbeit wird in einer physikalischen Fußballsimulation evaluiert. Im zweiten Teil dieser Dissertation werden Methoden zur Planung und Hindernisvermeidung von Multikoptern behandelt. Um die Planungskomplexität zu reduzieren, wird das zu lösenden Planungsproblem hierarchisch zerlegt und durch verschiedene Planungsebenen verarbeitet. Dabei haben höhere Planungsebenen eine abstraktere Weltsicht und werden mit niedriger Frequenz ausgeführt, zum Beispiel die Missionsplanung. Niedrigere Ebenen haben eine Weltsicht, die mehr den Sensordaten entspricht und werden mit höherer Frequenz ausgeführt. Die Granularität der resultierenden Pläne verfeinert sich hierbei auf niedrigeren Ebenen. Im Rahmen dieser Dissertation wurde eine komplette Planungshierarchie für Multikopter entwickelt, von Missionsplanern für verschiedene Anwendungsgebiete bis zu schneller Hindernisvermeidung. Pfade zur Ausführung geplanter Missionen werden durch zwei gekoppelte Planungsebenen erstellt, erst allozentrisch, und dann egozentrisch verfeinert. Hierbei werden ebenfalls globale und lokale Multiresolutionsrepräsentationen zur Beschleunigung der Planung eingesetzt. Zusätzlich zur Hindernisfreiheit und Länge der Pfade können auf diesen Planungsebenen weitere Zielfunktionen berücksichtigt werden, wie zum Beispiel die Berücksichtigung von Sensorcharakteristika. Ergänzt werden die Planungsebenen durch die Optimierung von Flugbahnen. Diese Flugbahnen berücksichtigen eine angenäherte Flugdynamik und erlauben damit ein schnelleres Verfolgen der optimierten Pfade. Um eine schnelle Konvergenz des Optimierungsproblems zu erreichen, wurde in dieser Arbeit ein Verfahren zur Initialisierung entwickelt. Des Weiteren kommen Methoden zur schnellen Verfeinerung des Optimierungsergebnisses bei Änderungen im Weltzustand zum Einsatz, diese ermöglichen die Reaktion auf neue Hindernisse oder Abweichungen von der Flugbahn, ohne eine komplette Flugbahn neu zu planen und zu optimieren. Die Sicherheit des durch die Planungs- und Optimierungsebenen erstellten Pfades wird durch eine schnelle, reaktive Hindernisvermeidung gewährleistet. Das Hindernisvermeidungsmodul basiert auf der Methode der künstlichen Potentialfelder. Durch die Verwendung dieser schnellen Methode kombiniert mit der Verwendung von nicht oder nur über kurze Zeiträume aggregierte Sensordaten, ermöglicht die Reaktion auf unbekannte Hindernisse, kurz nachdem diese von den Sensoren wahrgenommen wurden. Dabei kann der Multikopter abgebremst oder gestoppt werden, und sich von nähernden Hindernissen entfernen. Die Komponenten der Planungs- und Hindernisvermeidungshierarchie werden sowohl in der Simulation evaluiert, als auch in integrierten Gesamtsystemen mit verschiedenen Multikoptern in realen Anwendungen. Dies sind insbesondere die Kartierung von Innen- und Außenbereichen, die Inspektion von Gebäuden und Schornsteinen sowie die automatisierte Inventur von Lägern