Préhenseurs, conditions et stratégies pour une micromanipulation de précision

Mélanie Dafflon
EPFL, 2008
Thèse EPFL

Résumé

Currently microsystems consist of more and more functionalities in even smaller volumes. Components size has then to be reduced as well, coming through micro- and then nanoscale. The industrial equipments dedicated to their fabrication and assembly have comparatively a huge size, but one observes now a new and welcome trend for reducing their overall dimensions. However the latest robotic technologies allow achieving nanometric resolution and precision of positioning. Microcomponents assembly is still yet badly controlled and many surprising effects can occur without understanding of the real phenomenon. In fact, below one millimeter size objects are becoming insensitive to gravity comparing to surface forces. The manipulation of such components needs new and innovative ways to control these forces and so on to allow the release. In this study pick and place operations have been analyzed with an adimensional parameter Γ. It represents the ratio of the forces that act at the "object – gripper" and "object – target surface" interface. The adhesion effect is then taken into account in a comparative manner. The advantage of such procedure is due to the large amount of uncontrolled or unknown parameters that are needed to evaluate the adhesive forces. The behaviors of the micro object during pick and place operations are then studied on the base of Γ. Characteristics allowing a reliable transfer can be extracted with focus on the ones that generate fewer disturbances on the position. Generalization of the models allows finally to study different manipulation principles. The conception of microgrippers needs to consider the adhesion effects. Thus a methodology is proposed. Its main point concerns the importance of a strong interaction between the designers of the different elements that are the component, the receiver and the gripper. In such a way optimal choices for the surfaces and principles of manipulation can be done. After having defined the main trends theoretically, the difficult evaluation of the adhesion effect in real conditions causes the need to check rapidly by experiments the feasibility of the pick&place operations. A micromanipulation setup has been developed in order to make comparative tests between the different gripper principles. Gripper characterization means in particular the measurement of the positioning errors induced during the placing step. Several gripper families were conceived during this study: microtweezers, inertial gripper based on adhesion, capillary grippers that use the condensation/evaporation of the relative humidity, electrostatic grippers as well as vacuum gripper. Experiments were conducted with polystyrene spheres of ∅ 50µm. A high sensitivity to the alignment between finger tip or gripper tip and micro object was observed. It concerns in fact mainly the need to limit the force applied on the component during manipulation. The gripper withdrawal direction has also showed to be of the most importance to control the operations and their reliability. Finally robotic assembly of MEMS components was realized to get a 3D structure. The methodology was experimented on this application. The importance of a close interaction of the different designers has been demonstrated. We proposed here an approach as well as the models allowing studying the main trends with taking into account the adhesion forces. The whole arrangement of the contact areas as well as each force present during the operations is included into the models. The interfaces characteristics can so be analyzed. This allows defining the optimal strategy. This study is a tool for the designer of microassembly equipment. With the proposed methodology we hope or rather give the opportunity to stimulate integration or combination of innovative micromanipulation principles.

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https://infoscience.epfl.ch/record/125144?ln=fr

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Mélanie Dafflon
EPFL, 2008
Thèse EPFL

Résumé

Official source

https://infoscience.epfl.ch/record/125144?ln=fr

À propos de ce résultat

Concepts associés (14)

Concepts associés

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Publications associées (34)

Publications associées

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Motion Learning and Adaptive Impedance for Robot Control during Physical Interaction with Humans

Aude Billard, Elena Gribovskaya

One of the hallmarks of physical interaction between humans is haptic communication, i.e. an informa- tion exchange through force signals. Humans excel in tasks that require such interaction by adapting impedance and anticipating the partner’s intentions. It is highly desirable to endow robots with similar capabilities. Recently, the robotics community renewed its interest in variable impedance control. A special emphasis is put on the development of controllers that incorporate learning as an essential element. This article combines programming by demonstration and adaptive control for teaching a robot to physically interact with a human in a collaborative task requiring sharing of a load by the two partners. Learning a task model allows the robot to anticipate the partner’s intentions and adapt its motion according to perceived forces. As the human represents a highly complex contact environment, direct reproduction of the learned model may lead to sub-optimal results. To compensate for unmodelled uncertainties, in addition to learning we propose an adaptive control algorithm which tunes the impedance parameters, so as to ensure accurate reproduction. To simplify the illustration of the concepts introduced in this paper and provide a systematic evaluation, we present experimental results obtained in physically-realistic simulation of a dyad of two planar 2-DOF robots.

2011

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Humans demonstrate an impressive capability to manipulate fragile objects without damaging them, graciously controlling the force and position of hands or tools. Traditionally, robotics has favored position control over force control to produce fast, accurate and repeatable motion. For extending the applicability of robotic manipulators outside the strictly controlled environments of industrial work cells, position control is inadequate. Tasks that involve contact with objects whose positions are not known with perfect certainty require a controller that regulates the relationship between positional deviations and forces on the robot. This problem is formalized in the impedance control framework, which focuses the robot control problem on the interaction between the robot and its environment. By adjusting the impedance parameters, the behavior of the robot can be adapted to the need of the task. However, it is often difficult to specify formally how the impedance should vary for best performance. Furthermore, fast it can be shown that careless variation of the impedance can lead to unstable regulation or tracking even in free motion. In the first part of the thesis, the problem of how to define a varying impedance for a task is addressed. A haptic human-robot interface that allows a human supervisor to teach impedance variations by physically interacting with the robot during task execution is introduced. It is shown that the interface can be used to enhance the performance in several manipulation tasks. Then, the problem of stable control with varying impedance is addressed. Along with a theoretical discussion on this topic, a sufficient condition for stable varying stiffness and damping is provided. In the second part of the thesis, we explore more complex manipulation scenarios via online generation of the robot trajectory. This is done along two axes 1) learning how to react to contact forces in insertion tasks which are crucial for assembly operations and 2) autonomous Dynamical Systems (DS) for motion representation with the capability to encode a family of trajectories rather than a fixed, time-dependent reference. A novel framework for task representation using DS is introduced, termed Locally Modulated Dynamical Systems (LMDS). LMDS differs from existing DS estimation algorithms in that it supports non-parametric and incremental learning all the while guaranteeing that the resulting DS is globally stable at an attractor point. To combine the advantages of DS motion generation with impedance control, a novel controller for tasks described by first order DS is proposed. The controller is passive, and has the properties of an impedance controller with the added flexibility of a DS motion representation instead of a time-indexed trajectory.

EPFL2015

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Many manipulation tasks require coordinated motions for arm and fingers. Complexity increases when the task requires to control for the force at contact against a non-flat surface; This becomes even more challenging when this contact is done on a human. All these challenges are regrouped when one, for instance, massages a human limb. When massaging, the robotic arm is required to continuously adapt its orientation and distance to the limb while the robot fingers exert desired patterns of forces and motion on the skin surface. To address these challenges, we adopt a Dynamical System (DS) approach that offers a unified motion-force control approach and enables to easily coordinate multiple degrees of freedom. As each human limb may slightly differ, we learn a model of the surface using support vector regression (SVR) which enable us to obtain a distance-to-surface mapping. The gradient of this mapping, along with the DS, generates the desired motions for the interaction with the surface. A DS-based impedance control for the robotic fingers allows to control separately for force along the normal direction of the surface while moving in the tangential plane. We validate our approach using the KUKA IIWA robotic arm and Allegro robotic hand for massaging a mannequin arm covered with a skin-like material.We show that our approach allows for 1) reactive motion planning to reach for an unknown surface, 2) following desired motion patterns on the surface, and 3) exerting desired interaction forces profiles. Our results show the effectiveness of our approach; especially the robustness toward uncertainties for shape and the given location of the surface.

2020

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EPFL2015