Grasping, Perching, And Visual Servoing For Micro Aerial Vehicles

Micro Aerial Vehicles (MAVs) have seen a dramatic growth in the consumer market because of their ability to provide new vantage points for aerial photography and videography. However, there is little consideration for physical interaction with the environment surrounding them. Onboard manipulators are absent, and onboard perception, if existent, is used to avoid obstacles and maintain a minimum distance from them. There are many applications, however, which would benefit greatly from aerial manipulation or flight in close proximity to structures. This work is focused on facilitating these types of close interactions between quadrotors and surrounding objects. We first explore high-speed grasping, enabling a quadrotor to quickly grasp an object while moving at a high relative velocity. Next, we discuss planning and control strategies, empowering a quadrotor to perch on vertical surfaces using a downward-facing gripper. Then, we demonstrate that such interactions can be achieved using only onboard sensors by incorporating vision-based control and vision-based planning. In particular, we show how a quadrotor can use a single camera and an Inertial Measurement Unit (IMU) to perch on a cylinder. Finally, we generalize our approach to consider objects in motion, and we present relative pose estimation and planning, enabling tracking of a moving sphere using only an onboard camera and IMU

Towards Real-World Aerial Vision Guidance with Categorical 6D Pose Tracker

Tracking the object 6-DoF pose is crucial for various downstream robot tasks and real-world applications. In this paper, we investigate the real-world robot task of aerial vision guidance for aerial robotics manipulation, utilizing category-level 6-DoF pose tracking. Aerial conditions inevitably introduce special challenges, such as rapid viewpoint changes in pitch and roll and inter-frame differences. To support these challenges in task, we firstly introduce a robust category-level 6-DoF pose tracker (Robust6DoF). This tracker leverages shape and temporal prior knowledge to explore optimal inter-frame keypoint pairs, generated under a priori structural adaptive supervision in a coarse-to-fine manner. Notably, our Robust6DoF employs a Spatial-Temporal Augmentation module to deal with the problems of the inter-frame differences and intra-class shape variations through both temporal dynamic filtering and shape-similarity filtering. We further present a Pose-Aware Discrete Servo strategy (PAD-Servo), serving as a decoupling approach to implement the final aerial vision guidance task. It contains two servo action policies to better accommodate the structural properties of aerial robotics manipulation. Exhaustive experiments on four well-known public benchmarks demonstrate the superiority of our Robust6DoF. Real-world tests directly verify that our Robust6DoF along with PAD-Servo can be readily used in real-world aerial robotic applications

Concurrent, Integrated and Multicriteria Design Support for Mechatronic Systems

RÉSUMÉ Les systèmes mécatroniques sont une combinaison coopérative de composantes mécaniques, électroniques, de contrôle et logiciels. Dans les dernières décennies, Ils ont trouvé diverses applications dans l'industrie et la vie quotidienne. En raison de leur aspect multi-physique, du nombre élevé de leurs composantes et des interconnexions dynamiques entre les différents domaines impliqués dans leur fonctionnement, les dispositifs mécatroniques sont souvent considérés comme hautement complexes ce qui rend la tâche de les concevoir très difficile pour les ingénieurs. Cette complexité inhérente a attiré l’attention de la communauté de recherche en conception, en particulier dans le but d’atteindre une conception optimale des systèmes multi-domaines. Ainsi, cette thèse, représente une recherche originale sur le développement d'un paradigme de conception systématique, intégrée et multi-objectifs pour remplacer l'approche de conception séquentielle traditionnelle qui tend à traiter les différents domaines de la mécatronique séparément. Dans le but d'augmenter l'efficacité, la fiabilité, la facilité de contrôle et sa flexibilité, tout en réduisant la complexité et le coût effectif, ainsi que l'intégration systèmes, cette thèse présente de nouvelles approches pour la conception concurrente et optimale des systèmes mécatroniques aux stades de design conceptuel et détaillé. Les modèles mathématiques et les fondements qui soutiennent cette pensée sont présentés dans cette thèse. Les contributions des travaux de recherche de ce doctorat ont commencé par l'introduction d'un vecteur d'indices appelé le profile mécatronique multicritère (PMM) utilisé pour l'évaluation des concepts lors de la conception des systèmes mécatroniques. Les intégrales floues non linéaires de la théorie de décisions multicritères sont utilisées pour agréger les critères de conception et pour gérer les interactions possibles entre elles. Ensuite, une méthodologie de conception conceptuelle systématique est proposée et formulée. Le soutien à l'intégration d'outils d’aide à la décision multicritère dans le processus de conception est un autre objectif de cette thèse où un certain nombre de cadres de travail sont proposés pour aider les ingénieurs concepteurs à évaluer l’importance de certains critères et des paramètres d'interaction. Ces cadres de travail ne s'appliquent pas uniquement l'évaluation de la conception et de la conception optimales, mais aussi à la détermination des possibles façons d'améliorer les concepts développés. Des méthodes basées sur l’exploitation de données ainsi que des algorithmes d'optimisation sémantique sont utilisées pour identifier les paramètres flous avec le peu d’information disponibles sur les différents choix de concepts et les préférences des concepteurs.----------ABSTRACT Mechatronic systems are a combination of cooperative mechanical, electronics, control and software components. They have found vast applications in industry and everyday life during past decades. Due to their multi-physical aspect, the high number of their components, and the dynamic inter-connections between the different domains involved, mechatronic devices are often considered to be highly complex which makes the design task very tedious and non-trivial. This inherent complexity, has attracted a great deal of attention in the research community, particularly in the context of optimal design of multi-domain systems. To this end, the present thesis represents an original investigation into the development of a systematic, integrated and multi-objective design paradigm to replace the traditional sequential design approach that tends to deal with the different domains separately. With the aim of increasing efficiency, reliability, controllability and flexibility, while reducing complexity and effective cost, and finally facilitating system integration, this thesis presents new approaches towards concurrent and optimal design of mechatronic systems in conceptual and detailed design stages. The mathematical models and foundations which support this thinking are presented in the thesis. The contributions of our research work start with introducing an index vector called Mechatronic Multi-criteria Profile (MMP) used for concept evaluation in design of mechatronic systems. Nonlinear fuzzy integrals from multicriteria decision theory are utilized to aggregate design criteria and for handling possible interactions among them. Then, a systematic conceptual design methodology is proposed and formulated. Supporting the incorporation of multicriteria decision making tools into the design process, is another focus of this work where a number of frameworks are proposed to help the designers with assessment of criteria importance and interaction parameters. These frameworks are not only applicable in optimal design and design evaluation procedures, but also for determining possible ways for design improvements. Both data-driven methods as well as semantic-based optimization algorithms are used to identify the fuzzy parameters with limited available information about the design alternatives and designer preferences. Moreover, a fuzzy-based multi-objective approach has been undertaken for proposing and formulating a detailed design methodology. A unified performance evaluation index is introduced by the means of Choquet integrals and then optimized using a constrained particle swarm optimization (PSO) algorithm

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 344)

This bibliography lists 125 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during January, 1989. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

Recent Advances in Multi Robot Systems

To design a team of robots which is able to perform given tasks is a great concern of many members of robotics community. There are many problems left to be solved in order to have the fully functional robot team. Robotics community is trying hard to solve such problems (navigation, task allocation, communication, adaptation, control, ...). This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field. It is focused on the challenging issues of team architectures, vehicle learning and adaptation, heterogeneous group control and cooperation, task selection, dynamic autonomy, mixed initiative, and human and robot team interaction. The book consists of 16 chapters introducing both basic research and advanced developments. Topics covered include kinematics, dynamic analysis, accuracy, optimization design, modelling, simulation and control of multi robot systems

Underwater Vehicles

For the latest twenty to thirty years, a significant number of AUVs has been created for the solving of wide spectrum of scientific and applied tasks of ocean development and research. For the short time period the AUVs have shown the efficiency at performance of complex search and inspection works and opened a number of new important applications. Initially the information about AUVs had mainly review-advertising character but now more attention is paid to practical achievements, problems and systems technologies. AUVs are losing their prototype status and have become a fully operational, reliable and effective tool and modern multi-purpose AUVs represent the new class of underwater robotic objects with inherent tasks and practical applications, particular features of technology, systems structure and functional properties

Towards adaptive and autonomous humanoid robots: from vision to actions

Although robotics research has seen advances over the last decades robots are still not in widespread use outside industrial applications. Yet a range of proposed scenarios have robots working together, helping and coexisting with humans in daily life. In all these a clear need to deal with a more unstructured, changing environment arises. I herein present a system that aims to overcome the limitations of highly complex robotic systems, in terms of autonomy and adaptation. The main focus of research is to investigate the use of visual feedback for improving reaching and grasping capabilities of complex robots. To facilitate this a combined integration of computer vision and machine learning techniques is employed. From a robot vision point of view the combination of domain knowledge from both imaging processing and machine learning techniques, can expand the capabilities of robots. I present a novel framework called Cartesian Genetic Programming for Image Processing (CGP-IP). CGP-IP can be trained to detect objects in the incoming camera streams and successfully demonstrated on many different problem domains. The approach requires only a few training images (it was tested with 5 to 10 images per experiment) is fast, scalable and robust yet requires very small training sets. Additionally, it can generate human readable programs that can be further customized and tuned. While CGP-IP is a supervised-learning technique, I show an integration on the iCub, that allows for the autonomous learning of object detection and identification. Finally this dissertation includes two proof-of-concepts that integrate the motion and action sides. First, reactive reaching and grasping is shown. It allows the robot to avoid obstacles detected in the visual stream, while reaching for the intended target object. Furthermore the integration enables us to use the robot in non-static environments, i.e. the reaching is adapted on-the- fly from the visual feedback received, e.g. when an obstacle is moved into the trajectory. The second integration highlights the capabilities of these frameworks, by improving the visual detection by performing object manipulation actions