Adaptative grasp planning for manipulation of micro-objects

In the last several decades, optical tweezers have attracted much interest, and multiple methodologies have been proposed to accomplish various manipulation operations on cells or micro-particles. While typical optical tweezers use laser beams to directly trap and manipulate cells, various technolog...

Full description

Saved in:
Bibliographic Details
Main Author: Li, Jiuyun
Other Authors: Cheah Chien Chern
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/157782
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
Description
Summary:In the last several decades, optical tweezers have attracted much interest, and multiple methodologies have been proposed to accomplish various manipulation operations on cells or micro-particles. While typical optical tweezers use laser beams to directly trap and manipulate cells, various technologies have been proposed to facilitate grasping and manipulation of micro-objects. Considering  restricted capabilities of sensors and the existence of Brownian motion in the microworld, most grasping technologies have failed to tackle the current issues in the grasping process of micro-particles. Thus, some manual grasping methodologies have been used for automatic manipulation of micro-objects with arbitrary materials. The process is achieved by manually adjusting the microbeads or fingertips of the micro hands one by one, which is therefore a time-consuming process. To overcome the limitations of manual grasping, automatic grasping techniques for micro-objects are developed by controlling the formation of the trapped microbeads. However, these techniques do not consider the shapes or contours of the target objects in grasping, which is an important factor in achieving a feasible grasp. In this thesis, an adaptive grasp planning method is developed for grasping of micro-objects, where the shapes or contours of the target objects are considered in the grasping process. The sharper edges of target objects are automatically detected, and these sharper edges are avoided in the grasping technique. The proposed technique therefore enables the target micro-objects with both regular and irregular shapes to be grasped, and thus bringing robotic micro-manipulation closer to robotic manipulators in the physical world.