Positioning Fault Detection of a Piezoelectric-Driven Microrobot

Dumontier, F.; Santa, Karoly; Fatikow, Sergej

doi:10.1016/s1474-6670(17)42474-8

Cited by 6 publications

(3 citation statements)

References 3 publications

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“…A={e,G,sc,sL,n}, (14) where ® is the set of feasible configurations, G is the geometrical representation of A, SC describes all connections of P, SL describes physical constraints of the assembly process, UI is the set of all feasible assembly sequences. According to this model, the assembly planning of a microsystem A is defined as the process of generating a set UI based on the feasibility criteria and the given ®, G, sc and SL, and of selecting the optimal assembly sequence fl from the set 11 based on the optimization criteria.…”

Section: Microassembly Modelmentioning

confidence: 99%

<title>Planning and control of a microassembly process in a flexible microrobot-based desktop station</title>

Fatikow

Santa

1998

SPIE Proceedings

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There is an increasing interest in performing assembly of microsystems (i.e. non-destructive transportation, precise manipulation, and exact positioning of microcomponents) by flexible microrobots. A microrobot-based microassembly desktop station is being developed at the University of Karlsruhe. Several prototypes of piezoelectric driven microrobots and a design of the flexible microassembly desktop station were already presented at the last years' SPIE-meetings. In this paper, some implementation results of the station's planning and control system are presented. On the planning level, a common microassembly model for a computer-aidd assembly planning is suggested -which is based on geometric reasoning -and its components are discussed in detail. The feasibility criteria for the generation of feasible assembly sequences and the optimization criteria for selecting the optimal assembly plan are described. For stations employing several microrobots, a method for decomposition of an assembly plan is suggested. Since the station's microrobots are rather complicated systems, it is very hard to find a useful robot model for the control purposes. For this reason, control methods have to be used for positioning of a microrobot, which do not require an exact system model and which allow a reasonable compromise between the real-time processing and the exactness. An intelligent neural controller for positioning a microrobot has been developed.

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Section: Microassembly Modelmentioning

confidence: 99%

<title>Planning and control of a microassembly process in a flexible microrobot-based desktop station</title>

Fatikow

Santa

1998

SPIE Proceedings

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“…The most important problem is the inexact motion of the microrobot along the desired trajectory ( Fig. 3) [2]. Although the robot tries to walk along a calculated trajectory, the tip of its end-effector does not arrive at the target position under the microscope.…”

Section: Aspects Of the Microrobot's Mobilitymentioning

confidence: 99%

“…9 shows both the number of inputs of the neural model (2) and the number of outputs (1) and also the external feedback to generate a dynamic behavior.…”

Section: Development Of a Neural Controllermentioning

confidence: 99%

Control system for motion control of a piezoelectric micromanipulation robot

Santa

Fatikow

1998

Advanced Robotics

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Abstraet-Micromanipulation by microrobots has become an issue of primary importance in industry and biomedicine, since human manual capabilities are restricted to certain tolerances. The manipulation of biological cells or the assembly of a microsystem composed of several microcomponents are good examples. An automated microrobot-based micromanipulation desktop station has been developed at the University of Karlsruhe. The process of assembly takes place in the field of view of a light optical microscope. This paper focuses on motion control problems of the piezo-driven microrobots employed by the station. The ability to adapt itself to the process requirements is of great importance for micromanipulation robots. They must be able to operate in a partially defined environment and to ensure reasonable behavior in unpredicted situations. A neural control concept based on a reference model is proposed as a solution. It is shown that the neural controller is able to learn the desired behavior. It considerably outperforms an analytically designed linear controller in the real environment.

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Intelligente Ansteuerung von autonomen Mikrorobotern in einer Mikromanipulationsstation

Santa

Wörn

1997

Informatik Aktuell

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Positioning Fault Detection of a Piezoelectric-Driven Microrobot

Cited by 6 publications

References 3 publications

<title>Planning and control of a microassembly process in a flexible microrobot-based desktop station</title>

<title>Planning and control of a microassembly process in a flexible microrobot-based desktop station</title>

Control system for motion control of a piezoelectric micromanipulation robot

Intelligente Ansteuerung von autonomen Mikrorobotern in einer Mikromanipulationsstation

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