Kinematics of Redundantly Actuated Closed Chains

The instantaneous kinematics of a hybrid manipulation system, which combines the traditional serial chain geometry with parallelism in actuation, and the problem of coordination is discussed. The indeterminacy and singularities in the inverse kinematics and statics equations and measures of kinematic performance are analyzed. Finally, coordination algorithms that maintain an optimal force distribution between the actuators while avoiding or exploiting singularities are presented

Multi-robot cooperative platform : a task-oriented teleoperation paradigm

This thesis proposes the study and development of a teleoperation system based on multi-robot cooperation under the task oriented teleoperation paradigm: Multi-Robot Cooperative Paradigm, MRCP. In standard teleoperation, the operator uses the master devices to control the remote slave robot arms. These arms reproduce the desired movements and perform the task. With the developed work, the operator can virtually manipulate an object. MRCP automatically generates the arms orders to perform the task. The operator does not have to solve situations arising from possible restrictions that the slave arms may have. The research carried out is therefore aimed at improving the accuracy teleoperation tasks in complex environments, particularly in the field of robot assisted minimally invasive surgery. This field requires patient safety and the workspace entails many restrictions to teleoperation. MRCP can be defined as a platform composed of several robots that cooperate automatically to perform a teleoperated task, creating a robotic system with increased capacity (workspace volume, accessibility, dexterity ...). The cooperation is based on transferring the task between robots when necessary to enable a smooth task execution. The MRCP control evaluates the suitability of each robot to continue with the ongoing task and the optimal time to execute a task transfer between the current selected robot and the best candidate to continue with the task. From the operator¿s point of view, MRCP provides an interface that enables the teleoperation though the task-oriented paradigm: operator orders are translated into task actions instead of robot orders. This thesis is structured as follows: The first part is dedicated to review the current solutions in the teleoperation of complex tasks and compare them with those proposed in this research. The second part of the thesis presents and reviews in depth the different evaluation criteria to determine the suitability of each robot to continue with the execution of a task, considering the configuration of the robots and emphasizing the criterion of dexterity and manipulability. The study reviews the different required control algorithms to enable the task oriented telemanipulation. This proposed teleoperation paradigm is transparent to the operator. Then, the Thesis presents and analyses several experimental results using MRCP in the field of minimally invasive surgery. These experiments study the effectiveness of MRCP in various tasks requiring the cooperation of two hands. A type task is used: a suture using minimally invasive surgery technique. The analysis is done in terms of execution time, economy of movement, quality and patient safety (potential damage produced by undesired interaction between the tools and the vital tissues of the patient). The final part of the thesis proposes the implementation of different virtual aids and restrictions (guided teleoperation based on haptic visual and audio feedback, protection of restricted workspace regions, etc.) using the task oriented teleoperation paradigm. A framework is defined for implementing and applying a basic set of virtual aids and constraints within the framework of a virtual simulator for laparoscopic abdominal surgery. The set of experiments have allowed to validate the developed work. The study revealed the influence of virtual aids in the learning process of laparoscopic techniques. It has also demonstrated the improvement of learning curves, which paves the way for its implementation as a methodology for training new surgeons.Aquesta tesi doctoral proposa l'estudi i desenvolupament d'un sistema de teleoperació basat en la cooperació multi-robot sota el paradigma de la teleoperació orientada a tasca: Multi-Robot Cooperative Paradigm, MRCP. En la teleoperació clàssica, l'operador utilitza els telecomandaments perquè els braços robots reprodueixin els seus moviments i es realitzi la tasca desitjada. Amb el treball realitzat, l'operador pot manipular virtualment un objecte i és mitjançant el MRCP que s'adjudica a cada braç les ordres necessàries per realitzar la tasca, sense que l'operador hagi de resoldre les situacions derivades de possibles restriccions que puguin tenir els braços executors. La recerca desenvolupada està doncs orientada a millorar la teleoperació en tasques de precisió en entorns complexos i, en particular, en el camp de la cirurgia mínimament invasiva assistida per robots. Aquest camp imposa condicions de seguretat del pacient i l'espai de treball comporta moltes restriccions a la teleoperació. MRCP es pot definir com a una plataforma formada per diversos robots que cooperen de forma automàtica per dur a terme una tasca teleoperada, generant un sistema robòtic amb capacitats augmentades (volums de treball, accessibilitat, destresa,...). La cooperació es basa en transferir la tasca entre robots a partir de determinar quin és aquell que és més adequat per continuar amb la seva execució i el moment òptim per realitzar la transferència de la tasca entre el robot actiu i el millor candidat a continuar-la. Des del punt de vista de l'operari, MRCP ofereix una interfície de teleoperació que permet la realització de la teleoperació mitjançant el paradigma d'ordres orientades a la tasca: les ordres es tradueixen en accions sobre la tasca en comptes d'estar dirigides als robots. Aquesta tesi està estructurada de la següent manera: Primerament es fa una revisió de l'estat actual de les diverses solucions desenvolupades actualment en el camp de la teleoperació de tasques complexes, comparant-les amb les proposades en aquest treball de recerca. En el segon bloc de la tesi es presenten i s'analitzen a fons els diversos criteris per determinar la capacitat de cada robot per continuar l'execució d'una tasca, segons la configuració del conjunt de robots i fent especial èmfasi en el criteri de destresa i manipulabilitat. Seguint aquest estudi, es presenten els diferents processos de control emprats per tal d'assolir la telemanipulació orientada a tasca de forma transparent a l'operari. Seguidament es presenten diversos resultats experimentals aplicant MRCP al camp de la cirurgia mínimament invasiva. En aquests experiments s'estudia l'eficàcia de MRCP en diverses tasques que requereixen de la cooperació de dues mans. S'ha escollit una tasca tipus: sutura amb tècnica de cirurgia mínimament invasiva. L'anàlisi es fa en termes de temps d'execució, economia de moviment, qualitat i seguretat del pacient (potencials danys causats per la interacció no desitjada entre les eines i els teixits vitals del pacient). Finalment s'ha estudiat l'ús de diferents ajudes i restriccions virtuals (guiat de la teleoperació via retorn hàptic, visual o auditiu, protecció de regions de l'espai de treball, etc) dins el paradigma de teleoperació orientada a tasca. S'ha definint un marc d'aplicació base i implementant un conjunt de restriccions virtuals dins el marc d'un simulador de cirurgia laparoscòpia abdominal. El conjunt d'experiments realitzats han permès validar el treball realitzat. Aquest estudi ha permès determinar la influencia de les ajudes virtuals en el procés d'aprenentatge de les tècniques laparoscòpiques. S'ha evidenciat una millora en les corbes d'aprenentatge i obre el camí a la seva implantació com a metodologia d'entrenament de nous cirurgians.Postprint (published version

Representation and control of coordinated-motion tasks for human-robot systems

It is challenging for robots to perform various tasks in a human environment. This is because many human-centered tasks require coordination in both hands and may often involve cooperation with another human. Although human-centered tasks require different types of coordinated movements, most of the existing methodologies have focused only on specific types of coordination. This thesis aims at the description and control of coordinated-motion tasks for human-robot systems; i.e., humanoid robots as well as multi-robot and human-robot systems. First, for bimanually coordinated-motion tasks in dual-manipulator systems, we propose the Extended-Cooperative-Task-Space (ECTS) representation, which extends the existing Cooperative-Task-Space (CTS) representation based on the kinematic models for human bimanual movements in Biomechanics. The proposed ECTS representation can represent the whole spectrum of dual-arm motion/force coordination using two sets of ECTS motion/force variables in a unified manner. The type of coordination can be easily chosen by two meaningful coefficients, and during coordinated-motion tasks, each set of variables directly describes two different aspects of coordinated motion and force behaviors. Thus, the operator can specify coordinated-motion/force tasks more intuitively in high-level descriptions, and the specified tasks can be easily reused in other situations with greater flexibility. Moreover, we present consistent procedures of using the ECTS representation for task specifications in the upper-body and lower-body subsystems of humanoid robots in order to perform manipulation and locomotion tasks, respectively. Besides, we propose and discuss performance indices derived based on the ECTS representation, which can be used to evaluate and optimize the performance of any type of dual-arm manipulation tasks. We show that using the ECTS representation for specifying both dual-arm manipulation and biped locomotion tasks can greatly simplify the motion planning process, allowing the operator to focus on high-level descriptions of those tasks. Both upper-body and lower-body task specifications are demonstrated by specifying whole-body task examples on a Hubo II+ robot carrying out dual-arm manipulation as well as biped locomotion tasks in a simulation environment. We also present the results from experiments on a dual-arm robot (Baxter) for teleoperating various types of coordinated-motion tasks using a single 6D mouse interface. The specified upper- and lower-body tasks can be considered as coordinated motions with constraints. In order to express various constraints imposed across the whole-body, we discuss the modeling of whole-body structure and the computations for robotic systems having multiple kinematic chains. Then we present a whole-body controller formulated as a quadratic programming, which can take different types of constraints into account in a prioritized manner. We validate the whole-body controller based on the simulation results on a Hubo II+ robot performing specified whole-body task examples with a number of motion and force constraints as well as actuation limits. Lastly, we discuss an extension of the ECTS representation, called Hierarchical Extended-Cooperative-Task Space (H-ECTS) framework, which uses tree-structured graphical representations for coordinated-motion tasks of multi-robot and human-robot systems. The H-ECTS framework is validated by experimental results on two Baxter robots cooperating with each other as well as with an additional human partner

Manipulation Planning for Forceful Human-Robot-Collaboration

This thesis addresses the problem of manipulation planning for forceful human-robot collaboration. Particularly, the focus is on the scenario where a human applies a sequence of changing external forces through forceful operations (e.g. cutting a circular piece off a board) on an object that is grasped by a cooperative robot. We present a range of planners that 1) enable the robot to stabilize and position the object under the human applied forces by exploiting supports from both the object-robot and object-environment contacts; 2) improve task efficiency by minimizing the need of configuration and grasp changes required by the changing external forces; 3) improve human comfort during the forceful interaction by optimizing the defined comfort criteria. We first focus on the instance of using only robotic grasps, where the robot is supposed to grasp/regrasp the object multiple times to keep it stable under the changing external forces. We introduce a planner that can generate an efficient manipulation plan by intelligently deciding when the robot should change its grasp on the object as the human applies the forces, and choosing subsequent grasps such that they minimize the number of regrasps required in the long-term. The planner searches for such an efficient plan by first finding a minimal sequence of grasp configurations that are able to keep the object stable under the changing forces, and then generating connecting trajectories to switch between the planned configurations, i.e. planning regrasps. We perform the search for such a grasp (configuration) sequence by sampling stable configurations for the external forces, building an operation graph using these stable configurations and then searching the operation graph to minimize the number of regrasps. We solve the problem of bimanual regrasp planning under the assumption of no support surface, enabling the robot to regrasp an object in the air by finding intermediate configurations at which both the bimanual and unimanual grasps can hold the object stable under gravity. We present a variety of experiments to show the performance of our planner, particularly in minimizing the number of regrasps for forceful manipulation tasks and planning stable regrasps. We then explore the problem of using both the object-environment contacts and object-robot contacts, which enlarges the set of stable configurations and thus boosts the robot’s capability in stabilizing the object under external forces. We present a planner that can intelligently exploit the environment’s and robot’s stabilization capabilities within a unified planning framework to search for a minimal number of stable contact configurations. A big computational bottleneck in this planner is due to the static stability analysis of a large number of candidate configurations. We introduce a containment relation between different contact configurations, to efficiently prune the stability checking process. We present a set of real-robot and simulated experiments illustrating the effectiveness of the proposed framework. We present a detailed analysis of the proposed containment relationship, particularly in improving the planning efficiency. We present a planning algorithm to further improve the cooperative robot behaviour concerning human comfort during the forceful human-robot interaction. Particularly, we are interested in empowering the robot with the capability of grasping and positioning the object not only to ensure the object stability against the human applied forces, but also to improve human experience and comfort during the interaction. We address human comfort as the muscular activation level required to apply a desired external force, together with the human spatial perception, i.e. the so-called peripersonal-space comfort during the interaction. We propose to maximize both comfort metrics to optimize the robot and object configuration such that the human can apply a forceful operation comfortably. We present a set of human-robot drilling and cutting experiments which verify the efficiency of the proposed metrics in improving the overall comfort and HRI experience, without compromising the force stability. In addition to the above planning work, we present a conic formulation to approximate the distribution of a forceful operation in the wrench space with a polyhedral cone, which enables the planner to efficiently assess the stability of a system configuration even in the presence of force uncertainties that are inherent in the human applied forceful operations. We also develop a graphical user interface, which human users can easily use to specify various forceful tasks, i.e. sequences of forceful operations on selected objects, in an interactive manner. The user interface ties in human task specification, on-demand manipulation planning and robot-assisted fabrication together. We present a set of human-robot experiments using the interface demonstrating the feasibility of our system. In short, in this thesis we present a series of planners for object manipulation under changing external forces. We show the object contacts with the robot and the environment enable the robot to manipulate an object under external forces, while making the most of the object contacts has the potential to eliminate redundant changes during manipulation, e.g. regrasp, and thus improve task efficiency and smoothness. We also show the necessity of optimizing human comfort in planning for forceful human-robot manipulation tasks. We believe the work presented here can be a key component in a human-robot collaboration framework

Robot Manipulators

Robot manipulators are developing more in the direction of industrial robots than of human workers. Recently, the applications of robot manipulators are spreading their focus, for example Da Vinci as a medical robot, ASIMO as a humanoid robot and so on. There are many research topics within the field of robot manipulators, e.g. motion planning, cooperation with a human, and fusion with external sensors like vision, haptic and force, etc. Moreover, these include both technical problems in the industry and theoretical problems in the academic fields. This book is a collection of papers presenting the latest research issues from around the world

Softness Effects on Manipulability and Grasp Stability

This paper presents a novel analysis for the effects of softness at the fingertip on the manipulability and stability of grasping. The stability for grasping can be regarded that how much magnitude of external wrench we can balance. We formulate manipulability and the set of generable object wrenches for grasping system, taking deformation of the fingertips into consideration, and show that the increase of the softness decreases the manipulability while it increases generable object wrench. The validity of our analysis is shown by numerical examples. © 2011 IEEE

Trust-Based Control of Robotic Manipulators in Collaborative Assembly in Manufacturing

Human-robot interaction (HRI) is vastly addressed in the field of automation and manufacturing. Most of the HRI literature in manufacturing explored physical human-robot interaction (pHRI) and invested in finding means for ensuring safety and optimized effort sharing amongst a team of humans and robots. The recent emergence of safe, lightweight, and human-friendly robots has opened a new realm for human-robot collaboration (HRC) in collaborative manufacturing. For such robots with the new HRI functionalities to interact closely and effectively with a human coworker, new human-centered controllers that integrate both physical and social interaction are demanded. Social human-robot interaction (sHRI) has been demonstrated in robots with affective abilities in education, social services, health care, and entertainment. Nonetheless, sHRI should not be limited only to those areas. In particular, we focus on human trust in robot as a basis of social interaction. Human trust in robot and robot anthropomorphic features have high impacts on sHRI. Trust is one of the key factors in sHRI and a prerequisite for effective HRC. Trust characterizes the reliance and tendency of human in using robots. Factors within a robotic system (e.g. performance, reliability, or attribute), the task, and the surrounding environment can all impact the trust dynamically. Over-reliance or under-reliance might occur due to improper trust, which results in poor team collaboration, and hence higher task load and lower overall task performance. The goal of this dissertation is to develop intelligent control algorithms for the manipulator robots that integrate both physical and social HRI factors in the collaborative manufacturing. First, the evolution of human trust in a collaborative robot model is identified and verified through a series of human-in-the-loop experiments. This model serves as a computational trust model estimating an objective criterion for the evolution of human trust in robot rather than estimating an individual\u27s actual level of trust. Second, an HRI-based framework is developed for controlling the speed of a robot performing pick and place tasks. The impact of the consideration of the different level of interaction in the robot controller on the overall efficiency and HRI criteria such as human perceived workload and trust and robot usability is studied using a series of human-in-the-loop experiments. Third, an HRI-based framework is developed for planning and controlling the robot motion in performing hand-over tasks to the human. Again, series of human-in-the-loop experimental studies are conducted to evaluate the impact of implementation of the frameworks on overall efficiency and HRI criteria such as human workload and trust and robot usability. Finally, another framework is proposed for the cooperative manipulation of a common object by a team of a human and a robot. This framework proposes a trust-based role allocation strategy for adjusting the proactive behavior of the robot performing a cooperative manipulation task in HRC scenarios. For the mentioned frameworks, the results of the experiments show that integrating HRI in the robot controller leads to a lower human workload while it maintains a threshold level of human trust in robot and does not degrade robot usability and efficiency