Large-scale one-dimensional (1D) waveguide surface grating arrays enable smaller antenna pitches and larger apertures for the OPAs. However, broad wavelength tuning is required for wide-angle beam steering along the transverse θ direction for 1D waveguide antennas. High-resolution and wide-angle beam steerings at visible and NIR wavelengths have not been reported in previous studies. This study presents a large-scale SiNx nanophotonic phased array with an optical aperture of 2.3 mm × 2.3 mm, which is the largest OPA aperture produced in the visible and NIR bands thus far. Broad wavelength tuning from 650 nm to 1064 nm is employed to achieve small beam divergences of 0.03° – 0.054° in a wide steering range of 53.7°. The overall losses are accordingly analyzed with 3 dB bandwidth of 150 nm from 785 nm to 935 nm. Furthermore, with a supercontinuum laser illuminated on the OPA, more than 1000 resolvable spots merge together in the free space and form a fine strip of continuous line in the far-field projection with an FOV of >50°. This study demonstrates both high steering resolution and wide steering angle at wavelengths from visible to NIR on SiNx OPAs for the first time, to the best of our knowledge.

In this paper, we review the state of the art in hyper-redundant manipulators for applications in confined space such as on-orbit services. With their multiple degrees of freedom (DOF) and slender links, hyper-redundant manipulators can offer superior dexterity and excellent operability. They can traverse freely, manipulate objects flexibly, and conform to curvilinear paths accurately in confined spaces. The by-design separation of the mechanical and electrical parts in these manipulators also offers inherent structural compliance and miniaturization. Due to the elastic characteristics of driving cables, hyper-redundant manipulators have both stiffness and flexibility. In this paper, the overviews of the current state of the art in this field are provided from the perspectives of both typical applications and key technologies. We detailed the relevant studies on the configuration, obstacle avoidance, path planning, and control technologies for hyper-redundant manipulators and highlight the use of these studies in the development of practical applications. Furthermore, we propose several aspects that need to be further studied, namely efficient inverse kinematics solution, strong coupled dynamics modeling, variable stiffness control, and multi-objective trajectory optimization. Breakthroughs in these areas will provide valuable solutions for complex path planning and control of hyper-redundant manipulators.

An enclosed air-lift photobioreactor (ALPBR) is considered an efficient lab-scale bioreactor for microalgae cell growth and lipid biosynthesis. However, fluid-induced shear stress and mixing are two main factors that affect physiological metabolism in microalgal cell cultures. Herein, a 50-L ALPBR after being designed and manufactured was evaluated for microalgal suspension culture. Moreover, computational fluid dynamics (CFD) simulation was used to characterize the hydrodynamics of ALPBR. Specifically, two model microalgae species Chlorella vulgaris and Chlorella protothecoides were cultured with aeration rates at 0.1, 0.2, 0.3, 0.4 volume per volume per minute (vvm). The hydrodynamics of ALPBR while considering shear rate, volume average velocity, turbulent energy dissipation rate (EDR), air volume fraction, and mean air bubble diameter, etc. showed that aeration generated a very low shear stress. When C. protothecoides and C. vulgaris were cultured with various aeration rates, the maximum dry cell weights (DCW) of two microalgal species tested were 0.3 vvm and 0.2 vvm, while the maximum lipid contents of both species were about 15.0% of the DCW, which were achieved at an air flow rate of 0.2 vvm. Therefore, we concluded that the shear rate generated by aeration could play a vital role in the cell growth of microalgae grown in an air-lift photobioreactor.

Superior dexterity and extreme flexibility are typical advantages for concentric cable-driven manipulators working in confined spaces. However, its inverse kinematics and configuration planning are very complicated. In this article, we propose a spatial biarc method for the above problem. The distinguishing feature of this method is that input parameters are two positions and two direction vectors in three-dimensional (3-D) space, and the output is a reasonable spatial biarc for controlling a concentric cable-driven manipulator in 3-D space. This method has the following three advantages. First, the positions and direction vectors of the base and inner distal tip are considered simultaneously. In addition, the length and ratio of the overlapped section and separated section can be adjusted by changing the length of the direction vectors. Furthermore, by judging the angular value of the direction vectors, one can predetermine whether the spatial configuration of the entire arm is C- or S-shaped. The proposed method realizes the parameterization of a concentric cable-driven manipulator, which makes it convenient to intuitively control the manipulator to achieve interference-free motion trajectory planning in confined spaces. Finally, trajectory tracking inspections are simulated and experimentally executed. It can be seen from results that the proposed spatial biarc method can provide reasonable solutions for concentric cable-driven manipulators. The method is especially favorable in terms of 3-D-pose-determination problem and trajectory-planning problem. It can also be applied to other manipulators with similar configurations. Without loss of generality, when the given points and direction vectors are coplanar, the proposed spatial biarc method can be transformed to a planar biarc method.

Power lines are critical infrastructure components in power grid systems. Strand breakage is a kind of serious defect of power lines that can directly impact the reliability and safety of power supply. Due to the slender morphology of power lines and the difficulty in acquiring sufficient sample data, strand breakage detection remains a challenging task. Moreover, power grid corporations prefer to detect these defects on-site during power line inspection using unmanned aerial vehicles (UAVs), rather than transmitting all of the inspection data to the central server for offline processing which causes sluggish response and huge communication burden. According to the above challenges and requirements, this paper proposes a novel method for detecting broken strands on power lines in images captured by UAVs. The method features a multi-stage light-weight pipeline that includes power line segmentation, power line local image patch cropping, and patch classification. A power line segmentation network is designed to segment power lines from the background; thus, local image patches can be cropped along the power lines which preserve the detailed features of power lines. Subsequently, the patch classification network recognizes broken strands in the image patches. Both the power line segmentation network and the patch classification network are designed to be light-weight, enabling efficient online processing. Since the power line segmentation network can be trained with normal power line images that are easy to obtain and the compact patch classification network can be trained with relatively few positive samples using a multi-task learning strategy, the proposed method is relatively data efficient. Experimental results show that, trained on limited sample data, the proposed method can achieve an F1-score of 0.8, which is superior to current state-of-the-art object detectors. The average inference speed on an embedded computer is about 11.5 images per second. Therefore, the proposed method offers a promising solution for conducting real-time on-site power line defect detection with computing sources carried by UAVs.