Manipulation Of Micro-scale Objects Research Articles

Miniature Pneumatic Actuators for Soft Robots by High‐Resolution Multimaterial 3D Printing

AbstractMiniature soft robots offer excellent safety and deformability, which are highly desirable in applications such as navigation in confined areas or the manipulation of microscale objects. However, it is difficult to manufacture such robots using traditional processes due to the complexity of their design. While rapidly advancing 3D printing technologies offer manufacturing flexibility, it is still challenging to fabricate soft pneumatic robots on millimeter scales due to the difficulty in making microscale voids and channels, which are essential for pneumatic actuation. A generic process flow for systematic and efficient tailoring of the material formulation and key processing parameters for digital light processing‐based 3D printing of miniature pneumatic actuators for soft robots is presented. The process flow includes selection of photoabsorber and material performance characterization to determine the appropriate material formulation and characterizations for curing depth and XY fidelity to identify the combination of exposure time and sliced layer thickness. By applying the tailored results to a self‐built multimaterial 3D printing system, an assortment of miniature soft pneumatic robots with various structures and morphing modes are printed. Furthermore, potential applications of printed miniature actuators are exemplified by a soft debris remover that navigates in a confined space and collects small objects in a hard‐to‐reach position.

An Accurate Perception Method for Low Contrast Bright Field Microscopy in Heterogeneous Microenvironments

Automated optical tweezers-based robotic manipulation of microscale objects requires real-time visual perception for estimating the states, i.e., positions and orientations, of the objects. Such visual perception is particularly challenging in heterogeneous environments comprising mixtures of biological and colloidal objects, such as cells and microspheres, when the popular imaging modality of low contrast bright field microscopy is used. In this paper, we present an accurate method to address this challenge. Our method combines many well-established image processing techniques such as blob detection, histogram equalization, erosion, and dilation with a convolutional neural network in a novel manner. We demonstrate the effectiveness of our processing pipeline in perceiving objects of both regular and irregular shapes in heterogeneous microenvironments of varying compositions. The neural network, in particular, helps in distinguishing the individual microspheres present in dense clusters.

Evaluation of a monolithic piezoelectric drive unit for a miniature robot

In this paper, the evaluation of two different piezoelectric drive units developed for motion generation in a miniature robot is presented. The miniature robot is intended for high precision manipulation of microscale objects. The drive units have six drive elements integrated monolithically and each drive element is a three-axial multilayer piezoceramic actuator. This enables the robot to perform five-axial manipulation operations. Two inertial and two quasistatic walking mechanisms are evaluated. Due to the high level of miniaturisation the motion capacity of the drive elements is restrained. A fair step control is obtained for the inertial mechanisms while the quasistatic waveforms give a somewhat larger scatter. Walking mechanisms are expected to be advantageous at miniature scale, but the need for more complex motion patterns increases demands on design and fabrication. The height errors of the drive elements are believed to be the main reason for the larger variation in step length of the walking mechanisms. The inertial mechanisms appear to be affected by uncontrolled collisions between the drive elements and the moving body. With proper waveforms and optimised design all these undesired effects could be minimised and the second drive unit, which has an advantageous shape of the drive elements, demonstrates an improved behaviour.