Extrinsic Parameter Calibration Method for a Visual/Inertial Integrated System with a Predefined Mechanical Interface.

For a visual/inertial integrated system, the calibration of extrinsic parameters plays a crucial role in ensuring accurate navigation and measurement. In this work, a novel extrinsic parameter calibration method is developed based on the geometrical constraints in the object space and is implemented by manual swing. The camera and IMU frames are aligned to the system body frame, which is predefined by the mechanical interface. With a swinging motion, the fixed checkerboard provides constraints for calibrating the extrinsic parameters of the camera, whereas angular velocity and acceleration provides constraints for calibrating the extrinsic parameters of the IMU. We exploit the complementary nature of both the camera and IMU, of which the latter assists in the checkerboard corner detection and correction while the former suppresses the effects of IMU drift. The results of the calibration experiment reveal that the extrinsic parameter accuracy reaches 0.04° for each Euler angle and 0.15 mm for each position vector component (1σ).

Error Analysis and Calibration Method of a Multiple Field-of-View Navigation System.

The Multiple Field-of-view Navigation System (MFNS) is a spacecraft subsystem built to realize the autonomous navigation of the Spacecraft Inside Tiangong Space Station. This paper introduces the basics of the MFNS, including its architecture, mathematical model and analysis, and numerical simulation of system errors. According to the performance requirement of the MFNS, the calibration of both intrinsic and extrinsic parameters of the system is assumed to be essential and pivotal. Hence, a novel method based on the geometrical constraints in object space, called checkerboard-fixed post-processing calibration (CPC), is proposed to solve the problem of simultaneously obtaining the intrinsic parameters of the cameras integrated in the MFNS and the transformation between the MFNS coordinate and the cameras' coordinates. This method utilizes a two-axis turntable and a prior alignment of the coordinates is needed. Theoretical derivation and practical operation of the CPC method are introduced. The calibration experiment results of the MFNS indicate that the extrinsic parameter accuracy of the CPC reaches 0.1° for each Euler angle and 0.6 mm for each position vector component (1σ). A navigation experiment verifies the calibration result and the performance of the MFNS. The MFNS is found to work properly, and the accuracy of the position vector components and Euler angle reaches 1.82 mm and 0.17° (1σ) respectively. The basic mechanism of the MFNS may be utilized as a reference for the design and analysis of multiple-camera systems. Moreover, the calibration method proposed has practical value for its convenience for use and potential for integration into a toolkit.

Tough adhesion enhancing strategies for injectable hydrogel adhesives in biomedical applications.

Injectable hydrogel adhesives have gained widespread attention due to their ease of use, fast application time, and suitability for minimally invasive procedures. Several biomedical applications depend on tough adhesion between hydrogel adhesives and tissues, including wound closure and healing, hemostasis, tissue regeneration, drug delivery, and wearable electronic devices. Compared with bulk hydrogel adhesives formed ex situ, injectable hydrogel adhesives are more difficult to achieve strong adhesion strength due to a further balance of cohesion and adhesion while maintaining their flowability. In this review, the critical principles in designing tough adhesion of injectable hydrogel adhesives are summarized, including simultaneously enhancing their intrinsic interfacial toughness (Γ0inter) and mechanical dissipation (ΓDinter). Thereafter, various design strategies to enhance the Γ0inter and ΓDinter are discussed and evaluated respectively, involving multiple noncovalent/covalent interactions, topological connections, and polymer network structures. Furthermore, targeted biomedical applications of injectable hydrogel adhesives for specific tissue needs are systematically highlighted. In the end, this review outlines the challenges and trends in producing next-generation multifunctional injectable hydrogels for both practical and translational applications.

A novel fluorescent probe for the detection of nitric oxide in vitro and in vivo.

Fluorescence imaging of nitric oxide (NO) in vitro and in vivo is essential to developing our understanding of the role of nitric oxide in biology and medicine. Current probes such as diaminofluorescein depend on reactions with oxidized NO products, but not with nitric oxide directly, and this limits their applicability. Here we report the formation of an imaging probe for nitric oxide by coordinating the highly fluorescent chemical 4-methoxy-2-(1H-naphtho[2,3-d]imidazol-2-yl)phenol (MNIP) with Cu(II). The coordination compound MNIP-Cu reacts rapidly and specifically with nitric oxide to generate a product with blue fluorescence that can be used in vitro and in vivo. In the present study MNIP-Cu was used to reveal nitric oxide produced by inducible nitric oxide synthase in lipopolysaccharide (LPS)-activated macrophages (Raw 264.7 cells) and by endothelial nitric oxide synthase in endothelial cells (HUVEC). MNIP-Cu was also used to evaluate the distribution of nitric oxide synthesis in a model of acute liver injury induced by LPS and d-galactosamine in mice. The results demonstrate that MNIP-Cu can act as a novel fluorescent probe for nitric oxide and has many potential applications in biomedical research.

A 6-DOF Navigation Method based on Iterative Closest Imaging Point Algorithm.

To achieve six degree-of-freedom autonomous navigation of an inboard spacecraft, a novel algorithm called iterative closest imaging point (ICIP) is proposed, which deals with the pose estimation problem of a vision navigation system (VNS). This paper introduces the basics of the ICIP algorithm, including mathematical model, algorithm architecture, and convergence theory. On this basis, a navigation method is proposed. This method realizes its initialization using a Gaussian mixture model-based Kalman filter, which simultaneously solves the 3D-to-2D point correspondences and the camera pose. The initial value sensitivity, computational efficiency, robustness, and accuracy of the proposed navigation method are discussed based on simulation results. A navigation experiment verifies that the proposed method works effectively. The three-axis Euler angle accuracy is within 0.19° (1σ), and the three-axis position accuracy is within 1.87 mm (1σ). The ICIP algorithm estimates the full-state pose by merely finding the closest point couples respectively form the images obtained by the VNS and predicted at an initial value. Then the optimized solution of the imaging model is iteratively calculated and the full-state pose is obtained. Benefiting from the absence of a requirement for feature matching, the proposed navigation method offers advantages of low computational complexity, favorable stability, and applicability in an extremely simple environment in comparison with conventional methods.