This thesis is concerned with the development, design and implementation of a novel hybrid multi-agent orientated control architecture for navigation of multiple autonomous mobile robots operating in an unknown and unstructured environment populated by static and/or dynamic obstacles. The proposed hybrid control architecture is modular and draws its design from competitive tasks architecture, production rules architecture, connectionist architecture, dynamic system architecture, multi-agent architecture and subsumption architecture. The reasoning of the control architecture is both deliberative and reactive. The proposed reactive behaviours are modelled using fuzzy logic, neural networks and hybrid behavioural encoding incorporating stateflow-fuzzy logic and stateflow-neural networks. The deliberative system is comprised of finite state machines. The processing is achieved in a centralised and/or decentralised manner using the proposed controller-agent concept from the field of multi-agent systems. The framework of the control architecture is suitable for adaptation in single and multiple robot navigation. The control architecture has been implemented in MATLAB/Simulink using the full non-linear model of the MIABOT V2 mobile robots. It is evaluated incrementally in order to verify its overall control performance and the performance of each subsystem. Results show that the control architecture's modularity, distribution, reactivity and behaviourbased structure provided the overall control system with robustness in all cases of navigation tasks utilising either single or multiple mobile robots. Furthermore the results obtained show the effectiveness of the control architecture in navigation tasks involving up to five mobile robots operating in unknown static and dynamic environments. The results demonstrate that the control strategy chosen for navigation of multiple mobile robots is efficient and also established the robustness of the control system architecture against the desired requirements, such as supervision, decision-making and co-ordination of internal control structures (subsystems). The autonomous mobile robots were exposed to a complex and highly dynamic environment and successfully achieved every control objective. Their trajectories were smooth despite the interaction between several behaviours and the presence of unexpected static and dynamic obstacles. The main contributions of this thesis are: development of a novel hybrid multi-agent based control architecture called CARDS; novel approach for identification of direction of moving obstacles (other robots) using finite state machines; novel approach for behavioural encoding using hybrid solutions such as stateflow-fuzzy and stateflow-neural for autonomous robot navigation; proposed a design methodology for developing integrated solutions for autonomous mobile robotic systems and classification of the main design methodology (properties) of control systems architectures for autonomous mobile robots. Less significance contributions are: literature survey on approaches/methods related to the development of intelligent control architectures for navigation of multiple autonomous mobile robots; modelling of MIABOT V2 mobile robots; comparison between PI, fuzzy and neural controllers and algorithmic methodology for discovery of fuzzy/neural local models from observation data; identification of the relationship of the most important requirements/properties of control architecture versus the main control architecture specifications using the Quality Function Deployment tool; modular approach for modelling and evaluation of three types of sensor and sensor sensitivity.

Mechanical compliance will be an essential component for agile robots as they begin to leave the laboratory settings and join our world. The most crucial finding of this dissertation is showing how lessons learned from soft robotics can be adapted into traditional robotics to introduce compliance. Therefore, it presents practical knowledge on how to build soft bodied sensor and actuation modules: first example being soft-bodied curvature sensors. These sensors contain both standard electronic components soldered on flexible PCBs and hyperelastic materials that cover the electronics. They are built by curing multi-material composites inside hyper elastic materials. Then it shows, via precise sensing by using magnets and Hall-effect sensors, how closed-loop control of soft actuation modules can be achieved via proprioceptive feedback. Once curvature sensing idea is verified, the dissertation describes how the same sensing methodology, along with the same multi-material manufacturing technique can be utilized to construct soft bodied tri-axial force sensors. It shows experimentally that these sensors can be used by traditional robotic grippers to increase grasping quality. At this point, I observe that compliance is an important property that robots may utilize for different types of motions. One example being Raibert's 2D hopper mechanism. It uses its leg-spring to store energy while on the ground and release this energy before jumping. I observe that via soft material design, it would be possible to embed compliance directly into the linkage design itself. So I go over the design details of an extremely lightweight compliant five-bar mechanism design that can store energy when compressed via soft ligaments embedded in its joints. I experimentally show that the compliant leg design offers increased efficiency compared to a rigid counterpart. I also utilize the previously mentioned soft bodied force sensors for rapid contact detection (~5-10 Hz) in the hopper test platform. In the end, this thesis connects soft robotics with the traditional body of robotic knowledge in two aspects: a) I show that manufacturing techniques we use for soft bodied sensor/actuator designs can be utilized for creating soft ligaments that add strength and compliance to robot joints; and b) I demonstrate that soft bodied force sensing techniques can be used reliably for robotic contact detection.

Long, Qiaoxi. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references. / Abstracts in English and Chinese. / Abstract --- p.2 / 摘要 --- p.3 / Table of Contents --- p.4 / Acknowledgements --- p.6 / List of Figures --- p.7 / List of Tables --- p.9 / Chapter Chapter 1 --- Introduction --- p.10 / Chapter 1.1 --- Robot Soccer --- p.10 / Chapter 1.2 --- IRIP and IRIS --- p.11 / Chapter 1.3 --- Motivation and Literature Review --- p.14 / Chapter 1.4 --- Technical issues and Contributions --- p.15 / Chapter 1.5 --- Thesis Outline --- p.16 / Chapter Chapter 2 --- The IRIS system --- p.17 / Chapter 2.1 --- Hardware setup --- p.17 / Chapter 2.2 --- Software architecture --- p.21 / Chapter Chapter 3 --- Internet Accessibility --- p.26 / Chapter Chapter 4 --- Auto-charging --- p.32 / Chapter 4.1 --- Hardware setup --- p.33 / Chapter 4.2 --- Communication --- p.36 / Chapter 4.3 --- Vision --- p.41 / Chapter 4.4 --- Motion control --- p.44 / Chapter 4.4.1 --- APF --- p.44 / Chapter 4.4.2 --- CRC --- p.50 / Chapter 4.5 --- Processing Schemes --- p.51 / Chapter Chapter 5 --- Auto-Scoring and Auto-Judging --- p.56 / Chapter 5.1 --- Auto-scoring --- p.56 / Chapter 5.2 --- Auto-judging --- p.57 / Chapter 5.3 --- Judge robot --- p.59 / Chapter Chapter 6 --- Experimental Results --- p.63 / Chapter Chapter 7 --- Conclusions --- p.69 / Chapter 7.1 --- Summary --- p.69 / Chapter 7.2 --- Future work --- p.70 / Appendix A --- p.72 / Bibliography --- p.73

A aussi paru sous forme de thèse: Siegen, Univ., 2006.

Le corps humain a toujours été une source d’inspiration pour les ingénieurs et les scientifiques de tous les domaines dans le monde entier. L’un des sujets les plus intéressants de la dernière décennie a été les robots humanoïdes. Les robots humanoïdes représentent les systèmes robotiques les plus complexes. Ils offrent une plus grande mobilité dans les terrains accidentés et non structurés que les véhicules à roues normaux. À l’avenir, les robots humanoïdes devraient être employés pour une variété de tâches dangereuses dans des domaines tels que les opérations de sauvetage, l’assistance aux personnes âgées, l’éducation et le déminage humanitaire. Le travail réalisé dans cette thèse est réalisé sur le robot hydraulique humanoïde HYDROïD, un humanoïde à commande hydraulique avec 52 degrés de liberté actifs, conçu pour exécuter des tâches très dynamiques comme la marche, la course et le saut. robot puisque les actionneurs hydrauliques ont un excellent rapport poids/puissance et absorbent naturellement les pics de force d’impact lors des différentes activités. L'objectif de cette thèse est de contribuer au développement des mécanismes robotiques de la cheville et du genou avec une dynamique élevée. Un nouveau mécanisme de cheville est développé afin de pallier les inconvénients des performances réalisées avec l’ancien mécanisme de cheville d'origine. Des taux de fuite et de frottement plus faibles sont obtenus en plus d’une optimisation de pression pour les articulations de la cheville. De plus, une nouvelle solution pour optimiser le poids des actionneurs hydrauliques est appliquée sur le mécanisme du genou du robot.Une telle solution comprend l’utilisation de la technologie des matériaux composites légers pour atteindre un poids et une performance optimisés pour le joint. Afin d’appliquer des méthodologies de contrôle sur les mécanismes de la cheville et du genou, un modèle géométrique inverse pour les deux mécanismes est présenté. Le contrôle de position est utilisé pour contrôler les angles des articulations de la cheville et les mécanismes du genou. Enfin, les conclusions et les perspectives d’avenir sont présentées dans le dernier chapitre. / Human body has always been an inspiration for engineers and scientists from all fields all over the world. One of the most interesting topics in the last decade was humanoid robots. Humanoid robots represent the most complex robotic systems. They provide greater mobility in rough and unstructured terrain than the normal wheeled vehicles. In the future, humanoid robots are expected to be employed for a variety of dangerous tasks in fields like rescue operations, assisting elderly people, education and humanitarian demining. The work achieved in this dissertation is performed on the humanoid hydraulic robot HYDROïD. It is hydraulically actuated humanoid featuring 52 active degrees of freedom and is designed to perform highly dynamic tasks like walking, running and jumping. Hydraulic power was chosen for this robot since hydraulic actuators have an excellent power to weight ratio and naturally absorb impact force peaks during different activities. The objective of this dissertation is to contribute toward the development of ahighly dynamic robotic ankle and knee mechanisms. A new ankle mechanism islooked for in order to tackle the drawbacks raised by the performances achievedwith the original old ankle mechanism. Lower leakage and friction rates areachieved in addition to a pressure optimization for the ankle joints. Moreover, anew solution for optimizing the weight of hydraulic actuators is applied on theknee mechanism of the robot. Such solution includes the usage of light compositematerial technology to achieve optimized weight and performance for the joint.In order to apply control methodologies on the ankle and knee mechanisms,inverse geometrical model for the both mechanism are presented. Position controlis used to control the joints angles of the ankle and the knee mechanisms. Finally,the conclusions and the future perspectives are presented in the last chapter.

Les interfaces cerveau-ordinateur (ou BCI en anglais pour Brain-Computer Interfaces) mettent en place depuis le système nerveux central un circuit artificiel secondaire qui remplace l’utilisation des nerfs périphériques, permettant entre autres à des personnes ayant une déficience motrice grave d’interagir, uniquement à l’aide de leur activité cérébrale, avec différents types d’applications, tels qu’un système d’écriture, une neuro-prothèse, un fauteuil roulant motorisé ou un bras robotique. Une technique répandue au sein des BCI pour enregistrer l’activité cérébrale est l’électroencéphalographie (EEG), étant donné que contrairement à d’autres techniques d’imagerie, elle est non invasif et peu coûteuse. En outre, l’imagination motrice (MI), c’est-à-dire les oscillations des neurones du cortex moteur générées lorsque les sujets imaginent effectuer un mouvement sans réellement l’accomplir, est appropriée car détectable dans l’EEG et liée à l’activité motrice pour concevoir des interfaces comme des neuro-prothèses non assujetties à des stimuli. Cependant, même si des progrès importants ont été réalisés au cours des dernières années, un contrôle 3D complet reste un objectif à atteindre. Afin d’explorer de nouvelles solutions pour surmonter les limitations existantes, nous présentons une approche multiclasses qui considère la détection des imaginations motrices combinées. Le paradigme proposé comprend l’utilisation de la main gauche, de la main droite, et des deux pieds ensemble. Ainsi, par combinaison, huit commandes peuvent être fournies pour diriger un bras robotisé comprenant quatorze mouvements différents qui offrent un contrôle 3D complet. À cette fin, un système de commutation entre trois modes (déplacement du bras, du poignet ou des doigts) a été conçu et permet de gérer les différentes actions en utilisant une même commande. Ce système a été mis en oeuvre sur la plate-forme OpenViBE. En outre, pour l’extraction de caractéristiques une nouvelle approche de traitement d’information fournie par les capteurs a été développée sur la base de l’emplacement spécifique des sources d’activité liées aux parties du corps considérées. Cette approche permet de regrouper au sein d’une seule classe les différentes actions pour lesquelles le même membre est engagé, d’une manière que la tâche multiclasses originale se transforme en un problème équivalent impliquant une série de modèles de classification binaires. Cette approche permet d’utiliser l’algorithme de Common Spatial pattern (CSP) dont la capacité à discriminer des rythmes sensorimoteurs a été largement montrée mais qui présente l’inconvénient d’être applicable uniquement pour différencier deux classes. Nous avons donc également contribué à une nouvelle stratégie qui combine un ensemble de CSP et la géométrie riemannienne. Ainsi des caractéristiques plus discriminantes peuvent être obtenues comme les distances séparant les données des centres des classes considérées. Ces stratégies ont été appliquées sur trois nouvelles approches de classification qui ont été comparées à des méthodes de discrimination multiclasses classiques en utilisant les signaux EEG d’un groupe de sujets sains naïfs, montrant ainsi que les alternatives proposées permettent non seulement d’améliorer l’existant, mais aussi de réduire la complexité de la classification / Brain-Computer Interfaces (BCIs) replace the natural nervous system outputs by artificial ones that do not require the use of peripheral nerves, allowing people with severe motor impairments to interact, only by using their brain activity, with different types of applications, such as spellers, neuroprostheses, wheelchairs, or among others robotics devices. A very popular technique to record signals for BCI implementation purposes consists of electroencephalography (EEG), since in contrast with other alternatives, it is noninvasive and inexpensive. In addition, due to the potentiality of Motor Imagery (MI, i.e., brain oscillations that are generated when subjects imagine themselves performing a movement without actually accomplishing it) to generate suitable patterns for scheming self-paced paradigms, such combination has become a common solution for BCI neuroprostheses design. However, even though important progress has been made in the last years, full 3D control is an unaccomplished objective. In order to explore new solutions for overcoming the existing limitations, we present a multiclass approach that considers the detection of combined motor imageries, (i.e., two or more body parts used at the same time). The proposed paradigm includes the use of the left hand, right hand, and both feet together, from which eight commands are provided to direct a robotic arm comprising fourteen different movements that afford a full 3D control. To this end, an innovative switching-mode scheme that allows managing different actions by using the same command was designed and implemented on the OpenViBE platform. Furthermore, for feature extraction a novel signal processing scheme has been developed based on the specific location of the activity sources that are related to the considered body parts. This insight allows grouping together within a single class those conditions for which the same limb is engaged, in a manner that the original multiclass task is transformed into an equivalent problem involving a series of binary classification models. Such approach allows using the Common Spatial Pattern (CSP) algorithm; which has been shown to be powerful at discriminating sensorimotor rhythms, but has the drawback of being suitable only to differentiate between two classes. Based on this perspective we also have contributed with a new strategy that combines together the CSP algorithm and Riemannian geometry. In which the CSP projected trials are mapped into the Riemannian manifold, from where more discriminative features can be obtained as the distances separating the input data from the considered class means. These strategies were applied on three new classification approaches that have been compared to classical multiclass methods by using the EEG signals from a group of naive healthy subjects, showing that the proposed alternatives not only outperform the existing schema, but also reduce the complexity of the classification task