Path Planning for 3-D In-Hand Manipulation of Micro-Objects Using Rotation Decomposition

Abstract

Robotic manipulation and assembly of micro and nanocomponents in confined spaces is still a challenge. Indeed, the current proposed solutions that are highly inspired by classical industrial robotics are not currently able to combine precision, compactness, dexterity, and high blocking forces. In a previous work, we proposed 2-D in-hand robotic dexterous manipulation methods of arbitrary shaped objects that considered adhesion forces that exist at the micro and nanoscales. Direct extension of the proposed method to 3-D would involve an exponential increase in complexity. In this paper, we propose an approach that allows to plan for 3-D dexterous in-hand manipulation with a moderate increase in complexity. The main idea is to decompose any 3-D motion into a 3-D translation and three rotations about specific axes related to the object. The obtained simulation results show that 3-D in-hand dexterous micro-manipulation of arbitrary objects in presence of adhesion forces can be planned in just few seconds.

A Vision-Based Micro-Manipulation System

“…Micro-manipulation systems play a critical role in various scientific and industrial applications, enabling precise handling and control of microscopic objects. These systems have gained increasing importance in diverse fields such as biotechnology, materials science, and microelectronics, where the need for manipulating microscopic objects is constantly growing [1][2][3]. Precise micro-manipulation is essential, whether it involves the assembly of microelectronic components, the handling of biological samples, or the fabrication of micro-scale structures.…”

Space Detumbling Robot Arm Deployment Path Planning Based on Bi-FMT* Algorithm

“…Now, the solution for handling uncertainty is mainly divided into three categories. One is to optimize the design of a new spatial structure, as in [ 31 , 32 ]; another is to change the way of thinking and decompose the problem reasonably and abstractly, as explored by Kumar et al, where they decomposed any 3D motion into a 3D translation and three rotations about specific axes related to the object, which allows planning for 3D dexterous in-hand manipulation with a moderate increase in complexity in just a few seconds [ 33 ]; the third is to use probabilistic analysis methods. Sampling-based path planning achieves an optimal solution under probability analysis through a reduction in constraints and backward detection and evaluation, which can not only ensure the calculation efficiency but also deal with various constraints well.…”