Millirobots with magnetically drivable surfaces display a range of locomotive abilities and programmable behavior.

High-precision positioning is an essential requirement for sample operation at a small scale. At the current stage, although nanometer-scale accuracy has been achieved for the linear positioning, the rotational positioning (attitude control) is still very challenging and rarely addressed. This paper presents a rotatable nanorobotic system with rotational degrees of freedom first. Then, the system error, i.e., nonaxisymmetrical eccentricity error of the mechanism, is investigated dynamically and its fault model is established. After that, a double-loop servo repetitive controller is accordingly designed based on the circle interpolation strategy. The theoretical analysis and experimental results verify that the rotational positioning accuracy can be controlled up to submicrometers stably, which improves at least one order of magnitude than the current static method. Finally, two application cases are given to highlight the significance of this approach, i.e., surface defect detection from $\text{360}^{\circ }$ and in situ twisting characterization of 1-D micro/nanomaterial. This research paves a new avenue for the ultrahigh rotational positioning at microscopy environment, which is expected to generate a long-term impact on the micro/nanofields, such as microscopy imaging, material characterization, and so on.

Steering microswimmers toward 3-D autonomous manipulation tasks has received extensive attention. Our previous works have accomplished autonomously manipulating microswimmers in the 2-D space. This article aims to extend the 2-D autonomous manipulation to 3-D autonomous manipulation. Specifically, this article addresses the problem of an autonomous system that consists of 3-D path planning and 3-D path following for magnetically driven helical microswimmers. The path-planning algorithm called optimal Bidirectional RRT* is formulated to explore the shortest route in the confined 3-D space. A proxy-based sliding mode control (PSMC) approach is developed to design stable controllers based on the error model in the Serret–Frenet frame. We transport the swimming model trained by a kind of neural network to another new helical microswimmer according to an online updating scheme. The updating scheme can identify and refine compensating angles between the swimming direction of the microswimmer and the magnetic direction in the 3-D space facing the weight disturbances of the swimmer and lateral disturbances. The experiments are conducted to quantitatively validate the 3-D autonomous manipulation system. Experimental results show the effectiveness of path planning and path following with submillimeter accuracy in a 3-D space. Future works will focus on autonomous manipulations in dynamic environments. Note to Practitioners —This article is motivated by the issue of 3-D autonomous manipulation tasks for magnetically driven helical microswimmers. The formulated path planning is responsible for finding the shortest route in the 3-D confined space. The closed-loop controller is charge of steering the helical microswimmers on a reference path based on an online updating model trained by neural networks. It is demonstrated that the helical microswimmer can find the shortest path and follow it in a 3-D space with submillimeter accuracy.

Sensor drift is one of the severe issues that gas sensors suffer from. To alleviate the sensor drift problem, a gas sensor drift compensation approach is proposed based on local discriminant subspace projection (LDSP). The proposed approach aims to find a subspace to reduce the distribution difference between two domains, i.e., the source and target domain. Similar to domain regularized component analysis (DRCA) which is a recently proposed sensor drift correction method, the mean distribution discrepancy is minimized in the common subspace in our approach. LDSP extends DRCA in two aspects, i.e., it not only takes the label information of the source data into consideration to reduce the possibility of the case that samples in the subspace with different class labels stay close to each other, but also borrows the idea of locality-preserving projection to deal with multimodal data. Specifically, inspired by local Fisher discriminant analysis (LFDA), the label information is utilized to maximize the local between-class variance of source data in the latent common subspace and simultaneously minimize the local within-class variance. The formulation of LDSP is a generalized eigenvalue problem that can be readily solved. The experimental results have shown the proposed method outperforms other gas sensor drift compensation methods in terms of classification accuracy on two public gas sensor drift datasets.

Endovascular techniques have been increasingly adapted to medical applications as a minimally-invasive treatment approach to diagnose and treat various vascular diseases. Guidewires are the basic devices in endovascular surgery. The conventional practice of endovascular procedures has a number of drawbacks such as prolonged exposure to high doses of X-ray radiation, long operation time and undesired damage by surgeon’s unskilled operation. In this letter, we proposed a magnetically steerable guidewire and designed a three-dimensional magnetically actuating system. The proposed magnetically steerable guidewire consists of a commercial guidewire connecting to a soft actuator made of Ecoflex and magnetic powder. The actuating system contains two symmetrical parts, each consisting of three linear motors. It has great workspace of 700 mm × 500 mm × 500 mm, which can help the proposed guidewire to achieve a wide range of deflection angle. The relationship between the proposed guidewire’s deflection angle and the magnitude of the external magnetic field are explored, as well as the direction of the magnetic field. The proposed guidewire is flexible enough to make sharp turns up to 180 ${}^{\circ }$ in three dimensional workspace. The guidewire has achieved navigating through a set of rings and in a complex and constrained vascular phantom by programmed actuating magnetic fields.