A Cranial-Feature-Based Registration Scheme for Robotic Micromanipulation Using a Microscopic Stereo Camera System
Xiaofeng Lin, Sa\'ul Alexis Heredia P\'erez, Kanako Harada

TL;DR
This paper introduces a microscopic stereo camera system and a CNN-based registration scheme to improve robotic micromanipulation precision in biological applications, demonstrating high accuracy and real-time performance.
Contribution
The study presents a novel integration of MSCS with a CNN-based registration method for enhanced robotic manipulation of cranial surfaces.
Findings
MSCS achieved 0.10 mm precision and 30 FPS in 3D reconstruction.
Registration scheme had 1.13 mm translational and 3.38° rotational errors.
System demonstrated effective real-time performance in micromanipulation tasks.
Abstract
Biological specimens exhibit significant variations in size and shape, challenging autonomous robotic manipulation. We focus on the mouse skull window creation task to illustrate these challenges. The study introduces a microscopic stereo camera system (MSCS) enhanced by the linear model for depth perception. Alongside this, a precise registration scheme is developed for the partially exposed mouse cranial surface, employing a CNN-based constrained and colorized registration strategy. These methods are integrated with the MSCS for robotic micromanipulation tasks. The MSCS demonstrated a high precision of 0.10 mm 0.02 mm measured in a step height experiment and real-time performance of 30 FPS in 3D reconstruction. The registration scheme proved its precision, with a translational error of 1.13 mm 0.31 mm and a rotational error of 3.38 0.89 tested on…
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Taxonomy
MethodsSPEED: Separable Pyramidal Pooling EncodEr-Decoder for Real-Time Monocular Depth Estimation on Low-Resource Settings · Focus
