Symmetric Subspace Motion Generators

When moving an object endowed with continuous symmetry, an ambiguity arises in its underlying rigid body transformation, induced by the arbitrariness of the portion of motion that does not change the overall body shape. The functional redundancy caused by continuous symmetry is ubiquitously present in a broad range of robotic applications, including robot machining and haptic interface (revolute symmetry), remote center of motion devices for minimal invasive surgery (line symmetry), and motion modules for hyperredundant robots (plane symmetry). In this paper, we argue that such functional redundancy can be systematically resolved by resorting to symmetric subspaces (SSs) of the special Euclidean group SE(3), which motivates us to systematically investigate the structural synthesis of SS motion generators. In particular, we develop a general synthesis procedure that allows us to generate a wide spectrum of novel mechanisms for use in the applications mentioned

Adaptive and reconfigurable robotic gripper hands with a meso-scale gripping range

Grippers and robotic hands are essential and important end-effectors of robotic manipulators. Developing a gripper hand that can grasp a large variety of objects precisely and stably is still an aspiration even though research in this area has been carried out for several decades. This thesis provides a development approach and a series of gripper hands which can bridge the gap between micro-gripper and macro-gripper by extending the gripping range to the mesoscopic scale (meso-scale). Reconfigurable topology and variable mobility of the design offer versatility and adaptability for the changing environment and demands. By investigating human grasping behaviours and the unique structures of human hand, a CFB-based finger joint for anthropomorphic finger is developed to mimic a human finger with a large grasping range. The centrodes of CFB mechanism are explored and a contact-aided CFB mechanism is developed to increase stiffness of finger joints. An integrated gripper structure comprising cross four-bar (CFB) and remote-centre-of-motion (RCM) mechanisms is developed to mimic key functionalities of human hand. Kinematics and kinetostatic analyses of the CFB mechanism for multimode gripping are conducted to achieve passive-adjusting motion. A novel RCM-based finger with angular, parallel and underactuated motion is invented. Kinematics and stable gripping analyses of the RCM-based multi-motion finger are also investigated. The integrated design with CFB and RCM mechanisms provides a novel concept of a multi-mode gripper that aims to tackle the challenge of changing over for various sizes of objects gripping in mesoscopic scale range. Based on the novel designed mechanisms and design philosophy, a class of gripper hands in terms of adaptive meso-grippers, power-precision grippers and reconfigurable hands are developed. The novel features of the gripper hands are one degree of freedom (DoF), self-adaptive, reconfigurable and multi-mode. Prototypes are manufactured by 3D printing and the grasping abilities are tested to verify the design approach.EPSR

Flexible Object Manipulation

Flexible objects are a challenge to manipulate. Their motions are hard to predict, and the high number of degrees of freedom makes sensing, control, and planning difficult. Additionally, they have more complex friction and contact issues than rigid bodies, and they may stretch and compress. In this thesis, I explore two major types of flexible materials: cloth and string. For rigid bodies, one of the most basic problems in manipulation is the development of immobilizing grasps. The same problem exists for flexible objects. I have shown that a simple polygonal piece of cloth can be fully immobilized by grasping all convex vertices and no more than one third of the concave vertices. I also explored simple manipulation methods that make use of gravity to reduce the number of fingers necessary for grasping. I have built a system for folding a T-shirt using a 4 DOF arm and a fixed-length iron bar which simulates two fingers. The main goal with string manipulation has been to tie knots without the use of any sensing. I have developed single-piece fixtures capable of tying knots in fishing line, solder, and wire, along with a more complex track-based system for autonomously tying a knot in steel wire. I have also developed a series of different fixtures that use compressed air to tie knots in string. Additionally, I have designed four-piece fixtures, which demonstrate a way to fully enclose a knot during the insertion process, while guaranteeing that extraction will always succeed

Kinematic and anatomical measurement for biomechanical finger models

PhD ThesisBiomechanical models of the fingers are used to gain a greater understanding of their internal loading which will help guide clinicians treat injuries and pathologies. These models require accurate measurement of body kinematics, external reaction forces and anthropometry. The aim of this PhD was to gain a greater understanding of the predicted internal loading using biomechanical finger models and propose improvements in the kinematic and anatomical measurements required as their inputs. Through sensitivity analysis, correlations between uncertainty in the anthropometry and kinematics with predicted internal loading were found. This showed that the predicted internal loading was most sensitive to changes in the moment arm of the flexor digitorum profundus tendon. A new method of motion capture of the fingers using functionally defined joint centres was assessed. This method required the subject to complete a set of calibration movements. Subjects with an injury or pathology may have significantly reduced mobility, therefore an analysis was carried out to quantify the effect of reducing the available movement to that of a subject with pathological mobility. This resulted in errors of less than 5% in the predicted internal loading. It was important to note however, that in the extreme cases of deformity and lack of mobility this functional technique would not be suitable. Finally, a combined method of ultrasound and stereo-photogrammetry to measure the in-vivo moment arm of the flexor digitorum profundus was developed, enabling non-invasive subject specific measurements. Measurement made using this technique found moment arms within the range of previous studies but they were found to alter the predicted internal loading by up to 84%. This demonstrated the importance of subject specific measurement. Although this was only a pilot study with a single subject it showed how this technique could be applied not just to the fingers but to other parts of the body where subject specific measurements of moments arms are important

Virtual articulation and kinematic abstraction in robotics

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Cataloged from PDF version of thesis.Includes bibliographical references (p. 279-292).This thesis presents the theory, implementation, novel applications, and experimental validation of a general-purpose framework for applying virtual modifications to an articulated robot, or virtual articulations. These can homogenize various aspects of a robot and its task environment into a single unified model which is both qualitatively high-level and quantitatively functional. This is the first framework designed specifically for the mixed real/virtual case. It supports arbitrary topology spatial kinematics, a broad catalog of joints, on-line structure changes, interactive kinostatic simulation, and novel kinematic abstractions, where complex subsystems are simplified with virtual replacements in both space and time. Decomposition algorithms, including a novel method of hierarchical subdivision, enable scaling to large closed-chain mechanisms with 100s of joints. Novel applications are presented in two areas of current interest: operating high- DoF kinematic manipulation and inspection tasks, and analyzing reliable kinostatic locomotion strategies based on compliance and proprioception. In both areas virtual articulations homogeneously model the robot and its task environment, and abstractions structure complex models. For high-DoF operations the operator attaches virtual joints as a novel interface metaphor to define task motion and to constrain coordinated motion (by virtually closing kinematic chains); virtual links can represent task frames or serve as intermediate connections for virtual joints. For compliant locomotion, virtual articulations model relevant compliances and uncertainties, and temporal abstractions model contact state evolution.(cont.) Results are presented for experiments with two separate robotic systems in each area. For high-DoF operations, NASA/JPL's 36 DoF ATHLETE performs previously challenging coordinated manipulation/inspection moves, and a novel large-scale (100s of joints) simulated modular robot is conveniently operated using spatial abstractions. For compliant locomotion, two experiments are analyzed that each achieve high reliability in uncertain tasks using only compliance and proprioception: a novel vertical structure climbing robot that is 99.8% reliable in over 1000 motions, and a mini-humanoid that steps up an uncertain height with 90% reliability in 80 trials. In both cases virtual articulation models capture the essence of compliant/proprioceptive strategies at a higher level than basic physics, and enable quantitative analyses of the limits of tolerable uncertainty that compare well to experiment.by Marsette Arthur Vona, III.Ph.D

Grasp Stability Analysis with Passive Reactions

Despite decades of research robotic manipulation systems outside of highly-structured industrial applications are still far from ubiquitous. Perhaps particularly curious is the fact that there appears to be a large divide between the theoretical grasp modeling literature and the practical manipulation community. Specifically, it appears that the most successful approaches to tasks such as pick-and-place or grasping in clutter are those that have opted for simple grippers or even suction systems instead of dexterous multi-fingered platforms. We argue that the reason for the success of these simple manipulation systemsis what we call passive stability: passive phenomena due to nonbackdrivable joints or underactuation allow for robust grasping without complex sensor feedback or controller design. While these effects are being leveraged to great effect, it appears the practical manipulation community lacks the tools to analyze them. In fact, we argue that the traditional grasp modeling theory assumes a complexity that most robotic hands do not possess and is therefore of limited applicability to the robotic hands commonly used today. We discuss these limitations of the existing grasp modeling literature and setout to develop our own tools for the analysis of passive effects in robotic grasping. We show that problems of this kind are difficult to solve due to the non-convexity of the Maximum Dissipation Principle (MDP), which is part of the Coulomb friction law. We show that for planar grasps the MDP can be decomposed into a number of piecewise convex problems, which can be solved for efficiently. Despite decades of research robotic manipulation systems outside of highlystructured industrial applications are still far from ubiquitous. Perhaps particularly curious is the fact that there appears to be a large divide between the theoretical grasp modeling literature and the practical manipulation community. Specifically, it appears that the most successful approaches to tasks such as pick-and-place or grasping in clutter are those that have opted for simple grippers or even suction systems instead of dexterous multi-fingered platforms. We argue that the reason for the success of these simple manipulation systemsis what we call passive stability: passive phenomena due to nonbackdrivable joints or underactuation allow for robust grasping without complex sensor feedback or controller design. While these effects are being leveraged to great effect, it appears the practical manipulation community lacks the tools to analyze them. In fact, we argue that the traditional grasp modeling theory assumes a complexity that most robotic hands do not possess and is therefore of limited applicability to the robotic hands commonly used today. We discuss these limitations of the existing grasp modeling literature and setout to develop our own tools for the analysis of passive effects in robotic grasping. We show that problems of this kind are difficult to solve due to the non-convexity of the Maximum Dissipation Principle (MDP), which is part of the Coulomb friction law. We show that for planar grasps the MDP can be decomposed into a number of piecewise convex problems, which can be solved for efficiently. We show that the number of these piecewise convex problems is quadratic in the number of contacts and develop a polynomial time algorithm for their enumeration. Thus, we present the first polynomial runtime algorithm for the determination of passive stability of planar grasps. For the spacial case we present the first grasp model that captures passive effects due to nonbackdrivable actuators and underactuation. Formulating the grasp model as a Mixed Integer Program we illustrate that a consequence of omitting the maximum dissipation principle from this formulation is the introduction of solutions that violate energy conservation laws and are thus unphysical. We propose a physically motivated iterative scheme to mitigate this effect and thus provide the first algorithm that allows for the determination of passive stability for spacial grasps with both fully actuated and underactuated robotic hands. We verify the accuracy of our predictions with experimental data and illustrate practical applications of our algorithm. We build upon this work and describe a convex relaxation of the Coulombfriction law and a successive hierarchical tightening approach that allows us to find solutions to the exact problem including the maximum dissipation principle. It is the first grasp stability method that allows for the efficient solution of the passive stability problem to arbitrary accuracy. The generality of our grasp model allows us to solve a wide variety of problems such as the computation of optimal actuator commands. This makes our framework a valuable tool for practical manipulation applications. Our work is relevant beyond robotic manipulation as it applies to the stability of any assembly of rigid bodies with frictional contacts, unilateral constraints and externally applied wrenches. Finally, we argue that with the advent of data-driven methods as well as theemergence of a new generation of highly sensorized hands there are opportunities for the application of the traditional grasp modeling theory to fields such as robotic in-hand manipulation through model-free reinforcement learning. We present a method that applies traditional grasp models to maintain quasi-static stability throughout a nominally model-free reinforcement learning task. We suggest that such methods can potentially reduce the sample complexity of reinforcement learning for in-hand manipulation.We show that the number of these piecewise convex problems is quadratic in the number of contacts and develop a polynomial time algorithm for their enumeration. Thus, we present the first polynomial runtime algorithm for the determination of passive stability of planar grasps

Modellbasierte automatisierte Greifplanung

Die vorliegende Arbeit beschreibt das Planungssystem Auto GRASP zur modellbasierten, automatisierten Planung von Greifoperationen bekannter Objekte im Arbeitsraum eines Roboters. Im Gegensatz zu existierenden Greifplanungssystemen werden bei der Planung sämtliche erforderlichen Nebenbedingungen des Greifvorgangs berücksichtigt. Das vorgestellte Greifverfahren beruht auf einer effizienten Zweiteilung der Planung in eine Offline- und in eine Online-Phase. Während der Offline-Phase erfolgt eine maximale Modelldatenaufbereitung der zu greifenden Objekte. Geometrische Filteroperationen, die eine Art Shape-Matching zwischen der Geometrie des eingesetzten Parallelbackengreifers und der zu greifenden Objekte durchführen, generieren Griffklassen eines Objektes. Hierbei beschreibt eine Griffklasse eine Menge von Greifkoordinatensystemen, die für den Greifer unter konstanter Orientierung kollisionsfrei erreichbar sind. Als Orientierungen werden repräsentative Greiferorientierungen bestimmt, die zu Formschluß mit der Handbasis des Greifers und damit zu einer Erhöhung der Griffstabilität führen. Sämtliche generierten Griffklassen werden unter Berücksichtigung diverser geometrischer Kriterien bewertet, die aus den Ergebnissen der Modelldatenaufbereitung folgen. Daneben werden objektspezifische Merkmale bestimmt, die in die Online-Phase der Planung von Greifoperationen einfließen. Für die Planung evtl. erforderlicher Umgreifoperationen werden ebenfalls im Rahmen der Modelldatenaufbereitung Plazierungsklassen sämtlicher Objekte der Modellwelt generiert und evaluiert. Eine Plazierungsklasse eines Objektes beschreibt eine Menge von stabilen Plazierungen auf einer horizontalen Ablagefläche, die einen gemeinsamen Kontaktbereich besitzen. Zur Bewertung der Stabilität einer Plazierungsklasse wird eine anschaulich zu interpretierende Evaluierungsfunktion eingeführt. Die Ergebnisse der Modelldatenaufbereitung fließen in die Online-Phase der Planung von Greifoperationen ein.Grasping has evolved from a somewhat marginal topic to an important field in robotics research. This increasing interest in grasping is partly due to the increasing importance of flexible assembly in industrial automation. The thesis describes the model based grasp planning system Auto GRASP for automatically grasping objects in a robot’s workspace. In contrast to existing grasp planning systems various constraints are taken into account required for a successful execution of a grasp operation. The computations performed by Auto GRASP are split into offline and online computations, with as much a priori knowledge as possible used in the offline phase. During the offline phase a geometric grasp planning is performed using the concept of symbolic grasps. Symbolic grasps are generated by filter operations performing a kind of shape matching between the geometry of the gripper and the objects to be grasped. To reduce computational costs, representative gripper orientations are determined for each symbolic grasp. The new concept of representative gripper orientations guarantees, that the gripper’s palm can achieve form closure with the objects to be grasped. Thus, higher stability is achieved to resist dynamic disturbance forces arising during the motion of the robot. For each representative gripper orientation collision free approach trajectories and grasp frames are calculated in a local xy-configuration space respective to the objects. The resulting sets of grasp frames define grasp classes that are evaluated taking into account several evaluation criteria. For the generation of regrasp sequences, placement classes of objects are generated and evaluated. Placement classes describe stable object placements on a horizontal plane