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

International audienceThis 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

Advanced Characterization Techniques for Turbine Blade Wear and Damage

This paper presents four complementary non-destructive measurement techniques for material characterization and damage detection of turbine blades. The techniques are macroscopic fringe projection with inverse fringe projection algorithms, robot guided microscale fringe projection, high frequency eddy current and pulsed high frequency induction thermography, both in the megahertz range. The specimen on which the measurements were carried out is a blade of the 1st stage high pressure turbine of a modern airplane jet engine. The turbine blade was characterized with regard to the macroscopic and microscopic geometry, cracks in the base material as well as the condition of the protective layer system

Calibrating a Robot Camera

This paper addresses the problem of calibrating a camera mounted on a robot arm. The objective is to estimate the camera's intrinsic and extrinsic parameters. These include the relative position and orientation of camera with respect to robot base as well as the relative position and orientation of the camera with respect to a pre-defined world frame. A calibration object with a known 3D shape is used together with two known movements of the robot. A method is presented to find calibration parameters within an opti-misation framework. This method differs from existing methods in that 1) it fully exploits information from different displacements of the camera to produce an optimal calibration estimate, and 2) it uses an evolutionary algo-rithm to attain the optimal solution. Experimental results on both synthetic and real data are presented.

Hand-eye calibration for rigid laparoscopes using an invariant point

PURPOSE: Laparoscopic liver resection has significant advantages over open surgery due to less patient trauma and faster recovery times, yet it can be difficult due to the restricted field of view and lack of haptic feedback. Image guidance provides a potential solution but one current challenge is in accurate "hand-eye" calibration, which determines the position and orientation of the laparoscope camera relative to the tracking markers. METHODS: In this paper, we propose a simple and clinically feasible calibration method based on a single invariant point. The method requires no additional hardware, can be constructed by theatre staff during surgical setup, requires minimal image processing and can be visualised in real time. Real-time visualisation allows the surgical team to assess the calibration accuracy before use in surgery. In addition, in the laboratory, we have developed a laparoscope with an electromagnetic tracking sensor attached to the camera end and an optical tracking marker attached to the distal end. This enables a comparison of tracking performance. RESULTS: We have evaluated our method in the laboratory and compared it to two widely used methods, "Tsai's method" and "direct" calibration. The new method is of comparable accuracy to existing methods, and we show RMS projected error due to calibration of 1.95 mm for optical tracking and 0.85 mm for EM tracking, versus 4.13 and 1.00 mm respectively, using existing methods. The new method has also been shown to be workable under sterile conditions in the operating room. CONCLUSION: We have proposed a new method of hand-eye calibration, based on a single invariant point. Initial experience has shown that the method provides visual feedback, satisfactory accuracy and can be performed during surgery. We also show that an EM sensor placed near the camera would provide significantly improved image overlay accuracy