Three-dimensional (3D) enveloping grasps for dexterous robotic hands possess several advantages over other types of grasps. However, their innate characteristics such as the several degrees of freedom of the dexterous hand, complexity of analyzing the 3D geometry of the object to be grasped or detecting the 3D contact points between the object and the hand make planning them automatically a very challenging problem. This thesis describes a new method for kinematic 3D enveloping grasp planning for a three-fingered dexterous hand. The required inputs are the geometric models of the object and hand; and the kinematic model of the hand. The outputs are the position and orientation of the palm and the angular joint positions of the fingers. The method introduces a new way of processing the 3D object. Instead of considering the object as a whole, a series of 2D slices (vertical and horizontal) of the object are used to define its geometry. This method is considerably simpler than other methods of object modeling and its parameters can be easily setup. A new idea for grading the object's 3D grasp search domain is proposed. The grading system analyzes the curvature pattern and thickness of the object and grades object regions according to their suitability for grasping. The proposed method is capable of eliminating most of the ungraspable areas of the object from the grasp search domain at the early stages of the search. This improves the overall efficiency of the search for a grasp. In modeling a dexterous hand a new method is proposed to model the fingers. In this model each finger is modeled by three articulated line segments, representing the top, centre and bottom of the finger. This model has significant benefits that it is efficient and does not need the exact coordinate of the 3D contact point between the finger and the object to analyze the feasibility of the grasp. The new grasp planning method was implemented by writing a 4300 line MATLAB program. The program has been run successfully with several 3D objects. These results are documented. / Thesis / Master of Applied Science (MASc)

Dexterous manipulation operations using robotic or prosthetic fingers is seemingly facilitated with enhanced tactile feedback. Using a combination of artificial sensors and actuators, a tactile feedback system that conveys tactual information (force, pressure, & temperature) from an artificial fingertip to the user’s hand is developed and tested with subjects. Results reveal that subjects are capable of distinguishing specific actuators with a high degree of accuracy. The sensor density and actuator fidelity of the feedback system is insufficient to yield performance equal to that of a human’s natural tactile senses. Future studies are recommended to identify optimal tactile feedback sites as well as to discover a more robust system to be used in robotic and immersive virtual reality contexts.

Dexterous robotic manipulation of non-rigid objects is a challenging problem but necessary to explore as robots are increasingly interacting with more complex environments in which such objects are frequently present. In particular, common manipulation tasks such as molding clay to a target shape or picking fruits and vegetables for use in the kitchen, require a high-level understanding of the scene and objects. Commonly, the behavior of non-rigid objects is described by a model. Although, well-established modeling techniques are difficult to apply in robotic tasks since objects and their properties are unknown in such unstructured environments. This work proposes a sensing and modeling framework to measure the 3D shape deformation of non-rigid objects. Unlike traditional methods, this framework explores data-driven learning techniques focused on shape representation and deformation dynamics prediction using a graph-based approach. The proposal is validated experimentally, analyzing the performance of the representation model to capture the current state of the non-rigid object shape. In addition, the performance of the prediction model is analyzed in terms of its ability to produce future states of the non-rigid object shape due to the manipulation actions of the robotic system. The results suggest that the representation model is able to produce graphs that closely capture the deformation behavior of the non-rigid object. Whereas, the prediction model produces visually plausible graphs when short-term predictions are required.

The robotics community has succeeded in creating remarkable machines and task-level programming tools, but arguably has failed to apply sophisticated autonomous machines to sophisticated tasks. One reason is that this combination leads to prohibitive complexity. Biological systems provide many examples of integrated systems that combine high-performance and flexibility, with logically-organized low-level control. Sophisticated organisms have evolved that depend on physical dexterity to thrive in a particular ecological niche while mitigating computational and behavioral complexity. This dissertation investigates the potential for a new kind of hybrid robotic design process. A design for performance that combines mechanical dexterity with low-level embedded firmware that organizes behavior and facilitates programming at a higher level. I propose that dexterous machines can incorporate embedded firmware that express the "aptitudes'' implicit in the design of the robot and hierarchically organize the behavior of the system for programming. This is a win-win situation where the quality of the embedded firmware determines how efficiently programmers (autonomous learning algorithms or human programmers) can construct control programs that are robust, flexible, and respond gracefully to unanticipated circumstances. This dissertation introduces the uBot-5---a mobile manipulator concept for human environments that provides dexterous modes for mobility and manipulation and control firmware that organizes these behavioral modes locally for use by applications code. Postural control underlies the uniform treatment of several mobility modes that engage different combinations of sensory and motor resources. The result is a platform for studying "whole-body'' control strategies that can be applied jointly to simultaneous mobility and manipulation objectives. The thesis examines the specification and development of both: (1) a dexterous robot for unstructured environments, and (2) the embedded firmware that organizes dexterous behavior for mobility and manipulation tasks. Integrated solutions are proposed that control transitions between postural "modes'' and provide a logically organized dexterous behavior hierarchy. Firmware programming can also be used to construct an efficient API for user programming and autonomous machine learning. My goal is to contribute technologies that can support new robotic applications in our culture that require fully integrated dexterous robots in unstructured environments. Personal robotics is an important emerging application that depends on seamlessly integrated and sophisticated machines, controllers, and adaptability. Logically organized representations for use in task-level application development are critical to pull this off. The impact of such technology could be significant---with applications that include healthcare and telemedicine, exploration, emergency response, logistics, and flexible manufacturing.

abstract: Humans are capable of transferring learning for anticipatory control of dexterous object manipulation despite changes in degrees-of-freedom (DoF), i.e., switching from lifting an object with two fingers to lifting the same object with three fingers. However, the role that tactile information plays in this transfer of learning is unknown. In this study, subjects lifted an L-shaped object with two fingers (2-DoF), and then lifted the object with three fingers (3-DoF). The subjects were divided into two groups--one group performed the task wearing a glove (to reduce tactile sensibility) upon the switch to 3-DoF (glove group), while the other group did not wear the glove (control group). Compensatory moment (torque) was used as a measure to determine how well the subject could minimize the tilt of the object following the switch from 2-DoF to 3-DoF. Upon the switch to 3-DoF, subjects wearing the glove generated a compensatory moment (Mcom) that had a significantly higher error than the average of the last five trials at the end of the 3-DoF block (p = 0.012), while the control subjects did not demonstrate a significant difference in Mcom. Additional effects of the reduction in tactile sensibility were: (1) the grip force for the group of subjects wearing the glove was significantly higher in the 3-DoF trials compared to the 2-DoF trials (p = 0.014), while the grip force of the control subjects was not significantly different; (2) the difference in centers of pressure between the thumb and fingers (ΔCoP) significantly increased in the 3-DoF block for the group of subjects wearing the glove, while the ΔCoP of the control subjects was not significantly different; (3) lastly, the control subjects demonstrated a greater increase in lift force than the group of subjects wearing the glove (though results were not significant). Combined together, these results suggest different force modulation strategies are used depending on the amount of tactile feedback that is available to the subject. Therefore, reduction of tactile sensibility has important effects on subjects' ability to transfer learned manipulation across different DoF contexts. / Dissertation/Thesis / M.S. Bioengineering 2014

This thesis presents the development of an instrumented compliant wrist mechanism which serves as an interface between robotic platforms and their environments in order to detect surface positions and orientations. Although inspired by similar existing devices, additional features such as noncontact distance estimations, a simplified physical structure, and wireless operation were incorporated into the design. The primary role envisioned for this mechanism was for enabling robotic manipulators to perform surface following tasks prior to contact as this was one requirement of a larger project involving inspection of surfaces. The information produced by the compliant wrist system can be used to guide robotic devices in their workspace by providing real-time proximity detection and collision detection of objects. Compliance in robotic devices has attracted the attention of many researchers due to the multitude of benefits it offers. In the scope of this work, the main advantage of compliance is that it allows rigid structures to come into contact with possibly fragile objects. Combined with instrumentation for detecting the deflections produced by this compliance, closed-loop control can be achieved, increasing the number of viable applications for an initially open-loop system. Custom fabrication of a prototype device was completed to physically test operation of the designed system. The prototype incorporates a microcontroller to govern the internal operations of the device such as sensor data collection and processing. By performing many computation tasks directly on the device, robotic controllers are able to dedicate more of their time to more important tasks such as path planning and object avoidance by using the pre-conditioned compliant device data. Extensive work has also gone into the refinement of sensor signals coming from the key infrared distance measurement sensors used in the device. A calibration procedure was developed to decrease inter-sensor variability due to the method of manufacturing of these sensors. Noise reduction in the signals is achieved via a digital filtering process. The evaluation of the performance of the device is achieved through the collection of a large amount of sensor data for use in characterisation of the sensor and overall system behavior. This comes in the form of a statistical analysis of the sensor outputs to determine signal stability and accuracy. Additionally, the operation of the device is validated by its integration onto a manipulator robot and incorporating the data generated into the robot’s control loop.

L’objectif de cette thèse est de développer de nouveaux robots qui combinent dextérité, compacité et précision afin de réaliser des tâches de micromanipulation complexes dans des environnements confinés. Ainsi, deux architectures robotiques parallèles ont été développées. La première est un poignet à 4 degrés de liberté (DDL) en rotation et la seconde est un robot redondant à 7 DDL. Les deux structures intègrent la fonction de préhension grâce à une plateforme configurable et un actionnement déporté. L’étude géométrique et cinématique des deux robots ainsi que des résultats expérimentaux validant les deux architectures sont présentés. Pour miniaturiser le robot à 7 DDL, les liaisons mécaniques (rotules) ont été remplacées par des liaisons en élastomère (PDMS). Cette solution permet, entre autres, d’éliminer les jeux mécaniques au niveau des articulations tout en gardant une grande plage de déplacement. Cependant, comme le comportement de telles articulations ne correspond pas parfaitement à des liaisons rotules, un modèle de robot prenant en compte le comportement élastique de ces articulations a été développé. Afin de réaliser la structure à l’échelle désirée (jambes et liaisons à 400 µm de côté), un nouveau processus de micro-fabrication en salle blanche a été développé. Contrairement aux méthodes existantes, le nouveau processus permet de réduire le nombre d’étapes de gravure et d’intégrer différents types d’élastomères à des microstructures robotiques en silicium. Enfin, le micro-robot a été réalisé et les capacités de déplacement dans les 6 DDL en plus de la préhension ont été validées. Les applications visées des robots développées dans cette thèse sont le micro/nano-assemblage, la manipulation de cellules biologiques et la chirurgie mini-invasive, notamment en neurochirurgie. / The objective of this thesis is the development of new robots that combine dexterity, compactness and precision to perform complex micromanipulation tasks in confined environments. Thus, two parallel robotic structures have been developed. The first is a wrist that can insure 4 degrees of freedom (DOF) in rotation and the second is a redundant robot with 7 DOF. Both structures integrate the grasping function thanks to a configurable platform and a deported actuation. The kinematic study of the two robots and the experimental results validating the two architectures are presented. To miniaturize the 7 DOF robot, the mechanical joints (spherical) have been replaced by elastomeric articulations (PDMS). This solution allows, among others, to eliminate the mechanical backlash in the joints while keeping a large range of movements. However, as the behavior of such joints does not correspond perfectly to spherical joints, a model for the robot taking into account the elastic behavior of these joints has been developed. In order to made the structure on the desired scale (the cross sectional side of its legs and connections are 400 µm), a new microfabrication process in the clean room has been developed. Unlike the existing methods, the new process reduces the number of etching steps and allow the integration of different types of elastomers into silicon robotic microstructures. Finally, the micro-robot was realized and the displacement capacities in the 6 DOF with the grasping were validated. The targeted applications by the developed robots in this thesis are micro / nano-assembly, manipulation of biological cells and minimally invasive surgery, particularly in neurosurgery.

This thesis presents several new techniques for developing safe and flexible human-robot interaction tasks where human operators cooperate with robotic manipulators. The contributions of this thesis are divided in two fields: the development of safety strategies which modify the normal behavior of the robotic manipulator when the human operator is near the robot and the development of dexterous manipulation tasks for in-hand manipulation of objects with a multi-fingered robotic hand installed at the end-effector of a robotic manipulator. / Valencian Government by the research project "Infraestructura 05/053". Spanish Ministry of Education and Science by the pre-doctoral grant AP2005-1458 and the research projects DPI2005-06222 and DPI2008-02647, which constitute the research framework of this thesis.

Research and development leading to the realisation of a fully autonomous and robust multi-fingered hand has been going on for three decades. Yet none can be found in an industrial application. This is largely because we do not fully understand the fundamental mechanics of multi-finger grasping. / This thesis is a study of the mechanics of multi-finger grasping, with particular attention being paid to applying the analysis to experimental co-operative motion tasks between a hand-arm system and grasped object. / Fine manipulation with multi-fingered robot hands is critically influenced by the capacity to achieve stable grasps. By exploring the fundamental mechanics involved, a method for establishing the stability of spatial four finger-contact grasps is obtained. This work examines both frictionless and frictional grasps in two and three dimensions and develops the stability requirements for grasping. The conditions for a stable grasp are expressed as simple equations relating the line coordinates of (i) transitory sliding actuator and (ii) the normal to the tangent plane at every contact location. This is achieved by using the principle of virtual work and a branch of statics known as astatics. / After specifying a grasp in terms of its contact locations and forces the object can be grasped. However, in general the configuration of the hand-arm combination will not be unique, as such a manipulator system has more than six degrees of freedom and is said to be super-abundant. The choice of appropriate shares taken by the arm and hand in delivering the manipulation task needs to be resolved. This can be done making use of a kinematic performance measure based on aligning the grip triangle with the hand line of symmetry and maximising the available manipulation range. The hand-arm combination can then be driven to this desired grasp enabling the manipulator to carry out the specified task effectively. A Salisbury hand and PUMA 760 robot arm are used to demonstrate these co-operative motion tasks. / All the experimental results are presented along with a detailed description of the implementation of a hierarchical robot controller system which incorporates force control of the PUMA 760.

Ce travail s’inscrit dans le cadre de la conception et réalisation d’un robot d’assistance à la personne. Dans cette thèse, nous nous intéressons particulièrement à la conception, à la modélisation et à la commande d’un robot manipulateur mobile. La conception mécanique couplée à un outil de simulation dynamique multi-corps nous a permis d’obtenir un modèle virtuel très réaliste. Le modèle cinématique du système a été obtenu en utilisant la méthode D-H modifiée. L’approche Bond graph et la méthode de Lagrange ont permis de construire le modèle dynamique. Un algorithme hybride qui combine la pseudoinverse du jacobien et la méthode RRT a été proposé pour la planification de mouvement d’un manipulateur redondant et rechercher de configurations continues, stables et sans collision. Un contrôleur basé sur les réseaux de neurones a été introduit pour la commande coordonnée d’un manipulateur mobile. Cette méthode ne nécessite pas un modèle précis du robot. Les paramètres inconnus sont identifiés et compensés en utilisant des réseaux de neurones RBF. Un algorithme de contrôle similaire est présenté pour la commande force/position d’un manipulateur mobile qui est soumis à des contraintes holonomes et nonholonomes. L’étude de la main robotique a été effectuée séparément avant d’être couplée au reste du système. Les modèles cinématique et dynamique du système main-objet ont été obtenus en utilisant les approches mathématiques et bond graph. Un algorithme est proposé afin d’assurer une prise ferme, éviter les dérapages et suivre les mouvements désirés. Les validations des modèles et des différentes lois de commande ont été effectuées grâce à la co-simulation Matlab/modèle virtuel / The purpose of this thesis is to design, model and control of a personal assistant robot used for domestic tasks. In order to make the robot’s design more efficient, a virtual simulation system is built using dynamic simulation software. The kinematic model is set up based on modified D-H principle. The dynamic model is built using the Lagrange theorem and elaborated in Matlab. We also employ an energy-based approach for modeling and its bond graph notation ensures encapsulation of functionality, extendibility and reusability of each element of the model. A hybrid algorithm of combining the Jacobian pseudoinverse algorithm with Rapidly-Exploring Random Tree method is presented for collision-free path planning of a redundant manipulator. An intelligent robust controller based on neural network is introduced for the coordinated control of a mobile manipulator. This method does not require an accurate model of the robot. Unknown dynamic parameters of the mobile platform and the manipulator are identified and compensated in closed-loop control using RBF neural network. A similar control algorithm is presented for coordinated force/motion control of a mobile manipulator suffering both holonomic and nonholonomic constraints. Kinematics and dynamics of a dexterous hand manipulating an object with known shape by rolling contacts are derived. A computed torque control algorithm is presented to ensure firm grip, avoid slippage and well track a given motion imposed to the object. The validation of models and different control laws were made by the co-simulation Matlab / virtual model