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Kinematics parameters estimation for an AFM/robot integrated micro-force measurement system

Conference Paper Micro-Manipulation II Artificial Intelligence · Robotics

Abstract

This paper introduces a novel atomic force microscope (AFM) and parallel robot integrated micro-force measurement system whose objective is the measurement of adhesion force between planar micro-objects. This paper is mainly focused on the kinematics parameters estimation between the objects to be measured, the parallel robot and the AFM system in order to position both objects during measurement. A substrate is placed on the end-platform of the parallel robot system, on which three markers are utilized as the reference information to the kinematics parameters estimation. The markers are identified by the AFM scanning in order to identify the kinematics parameters of the whole system. Based on the classic Gauss-Newton algorithm, the position and orientation can be solved. Finally, the effectiveness of the proposed method is demonstrated through the experiments on the prototype of the micro-force measurement system. The parameters estimation methodology outlined is generic and also can be extended to a variety of applications in calibration of micro-robots.

Authors

Keywords

  • Substrates
  • Parallel robots
  • Mathematical model
  • Equations
  • Calibration
  • Kinematics
  • Parameter Estimates
  • Kinematic Parameters
  • Atomic Force Microscopy
  • Robotic System
  • Parallel System
  • Scanning Atomic Force Microscopy
  • Gauss-Newton Method
  • Scan In Order
  • Atomic Force Microscopy System
  • Unknown Parameters
  • Transformation Matrix
  • Detection Of Markers
  • Interaction Forces
  • Algebraic Equations
  • Motion Systems
  • Sine And Cosine
  • Vision Sensors
  • Atomic Force Microscopy Tip
  • Translation Vector
  • Independent Equations
  • World Frame
  • Reference Marker
  • Piezoelectric Stage
  • Parameter Estimation Process
  • Three-dimensional Equations
  • Micron Level
  • Atomic Force Microscopy Probe
  • Point In Frame
  • Degrees Of Freedom

Context

Venue
IEEE/RSJ International Conference on Intelligent Robots and Systems
Archive span
1988-2025
Indexed papers
26578
Paper id
823216184979010960
v2026.09.13