A two-phase gripper to reorient and grasp

This paper introduces the design of novel two-phase fingers to passively reorient objects while picking them up. Two-phase refers to a change in the finger-object contact geometry, from a free spinning point contact to a firm multipoint contact, as the gripping force increases. We exploit the two phases to passively reorient prismatic objects from a horizontal resting pose to an upright secure grasp. This problem is particularly relevant to industrial assembly applications where parts often are presented lying on trays or conveyor belts and need to be assembled vertically. Each two-phase finger is composed of a small hard contact point attached to an elastic strip mounted over a V-groove cavity. When grasped between two parallel fingers with low gripping force, the object pivots about the axis between the contact points on the strips, and aligns upright with gravity. A subsequent increase in the gripping force makes the elastic strips recede into the cavities letting the part seat in the V-grooves to secure the grasp. The design is compatible with any type of parallel-jaw gripper, and can be reconfigured to specific objects by changing the geometry of the cavity. The two-phase gripper provides robots with the capability to accurately position and manipulate parts, reducing the need for dedicated part feeders or time-demanding regrasp procedures.National Science Foundation (U.S.). National Robotics Initiative (NSF-IIS-1427050

Prehensile Pushing: In-hand Manipulation with Push-Primitives

This paper explores the manipulation of a grasped object by pushing it against its environment. Relying on precise arm motions and detailed models of frictional contact, prehensile pushing enables dexterous manipulation with simple manipulators, such as those currently available in industrial settings, and those likely affordable by service and field robots. This paper is concerned with the mechanics of the forceful interaction between a gripper, a grasped object, and its environment. In particular, we describe the quasi-dynamic motion of an object held by a set of point, line, or planar rigid frictional contacts and forced by an external pusher (the environment). Our model predicts the force required by the external pusher to “break” the equilibrium of the grasp and estimates the instantaneous motion of the object in the grasp. It also captures interesting behaviors such as the constraining effect of line or planar contacts and the guiding effect of the pusher’s motion on the objects’s motion. We evaluate the algorithm with three primitive prehensile pushing actions—straight sliding, pivoting, and rolling—with the potential to combine into a broader in-hand manipulation capability.National Science Foundation (U.S.). National Robotics Initiative (Award NSF-IIS-1427050)Karl Chang Innovation Fund Awar

A Multi-Sensorial Hybrid Control for Robotic Manipulation in Human-Robot Workspaces

Autonomous manipulation in semi-structured environments where human operators can interact is an increasingly common task in robotic applications. This paper describes an intelligent multi-sensorial approach that solves this issue by providing a multi-robotic platform with a high degree of autonomy and the capability to perform complex tasks. The proposed sensorial system is composed of a hybrid visual servo control to efficiently guide the robot towards the object to be manipulated, an inertial motion capture system and an indoor localization system to avoid possible collisions between human operators and robots working in the same workspace, and a tactile sensor algorithm to correctly manipulate the object. The proposed controller employs the whole multi-sensorial system and combines the measurements of each one of the used sensors during two different phases considered in the robot task: a first phase where the robot approaches the object to be grasped, and a second phase of manipulation of the object. In both phases, the unexpected presence of humans is taken into account. This paper also presents the successful results obtained in several experimental setups which verify the validity of the proposed approach

Grasping and Assembling with Modular Robots

A wide variety of problems, from manufacturing to disaster response and space exploration, can benefit from robotic systems that can firmly grasp objects or assemble various structures, particularly in difficult, dangerous environments. In this thesis, we study the two problems, robotic grasping and assembly, with a modular robotic approach that can facilitate the problems with versatility and robustness. First, this thesis develops a theoretical framework for grasping objects with customized effectors that have curved contact surfaces, with applications to modular robots. We present a collection of grasps and cages that can effectively restrain the mobility of a wide range of objects including polyhedra. Each of the grasps or cages is formed by at most three effectors. A stable grasp is obtained by simple motion planning and control. Based on the theory, we create a robotic system comprised of a modular manipulator equipped with customized end-effectors and a software suite for planning and control of the manipulator. Second, this thesis presents efficient assembly planning algorithms for constructing planar target structures collectively with a collection of homogeneous mobile modular robots. The algorithms are provably correct and address arbitrary target structures that may include internal holes. The resultant assembly plan supports parallel assembly and guarantees easy accessibility in the sense that a robot does not have to pass through a narrow gap while approaching its target position. Finally, we extend the algorithms to address various symmetric patterns formed by a collection of congruent rectangles on the plane. The basic ideas in this thesis have broad applications to manufacturing (restraint), humanitarian missions (forming airfields on the high seas), and service robotics (grasping and manipulation)

Sensitive Skin for Robotics

This thesis explores two novel ways of reducing the data complexity of tactile sensing. The thesis begins by examining the state-of-the art in tactile sensing, not only examining the sensor construction and interpretation of data but also the motivation for these designs. The thesis then proposes two methods for reducing the complexity of data in tactile sensing. The first is a low-power tactile sensing array exploiting a novel application of a pressure-sensitive material called quantum tunnelling composite. The properties of this material in this array form are shown to be beneficial in robotics. The electrical characteristics of the material are also explored. A bit-based structure for representing tactile data called Bitworld is then defined and its computational performance is characterised. It is shown that this bit-based structure outperforms floating-point arrays by orders of magnitude. This structure is then shown to allow high-resolution images to be produced by combining low resolution sensor arrays with equivalent functional performance to a floating-point array, but with the advantages of computational efficiency. Finally, an investigation into making Bitworld robust in the presence of positional noise is described with simulations to verify that such robustness can be achieved. Overall, the sensor and data structure described in this thesis allow simple, but effective tactile systems to be deployed in robotics without requiring a significant commitment of computational or power resources on the part of a robot designer.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Grasp planning for object manipulation by an autonomous robot

L'évolution autonome d'un robot dans un environnement évolutif nécessite qu'il soit doté de capacités de perception, d'action et de décision suffisantes pour réaliser la tâche assignée. Une tâche essentielle en robotique est la manipulation d'objets et d'outils. Elle intervient non seulement pour un robot seul mais également dans des situations d'interaction avec un humain ou un autre robot quand il s’agit d’échanger des objets ou de les manipuler conjointement.\ud Cette thèse porte sur la planification de tâches de manipulation d'objets pour un robot autonome dans un environnement humain. Une architecture logicielle susceptible de résoudre ce type de problèmes au niveau géométrique est proposée. Généralement, une tâche de manipulation commence par une opération de saisie dont la qualité conditionne fortement la réussite de la tâche et pour laquelle nous proposons un planificateur basé sur les propriétés inertielles de l'objet et une décomposition en éléments quasi-convexes tout en prenant en compte les contraintes imposées par le système mobile complet dans un environnement donné.\ud Les résultats sont validés en simulation et sur le robot sur la base d’une extension des outils de planification développés au LAAS-CNRS. Le modèle géométrique 3D de l’objet peut être connu a priori ou bien acquis en ligne. Des expérimentations menées sur un robot manipulateur mobile équipé d'une pince à trois points de contacts, de capteurs de force et d'une paire de caméras stéréoscopiques ont montré la validité de l'approche.\ud The autonomous robot performance in a dynamic environment requires advanced perception, action and decision capabilities. Interaction with the environment plays a key role for a robot and it is well illustrated in object and/or tool manipulation. Interaction with humans or others robots can consist in object exchanges.\ud This thesis deals with object manipulation planning by an autonomous robot in human environments. A software architecture is proposed that is capable to solve such problems at the geometrical level. In general, a manipulation task starts by a grasp operation which quality influences strongly the success of the overall task. We propose a planner based on object inertial properties and an approximate convex decomposition. The whole mobile system taken into account in the planning process.\ud The planner has been completely implemented as an extension of the planning tools developed at LAAS-CNRS. Its results have been tested in simulation and on a robotic platform. Object models may be known a priori or acquired on-line. Experiments have been carried out with a mobile manipulator equipped with a three fingers gripper, a wrist force sensor and a stereo camera system in order to validate the approach.\ud \ud \u