With the rapid advancement of intelligent unmanned aerial vehicle (UAV) technology, UAV swarm technology is being increasingly applied with autonomous control, intelligent collaboration, and flexible deployment. It exhibits tremendous potential in emergency rescue, environmental monitoring, wireless communication and other areas. UAV swarms require stable communication links to perform tasks such as formation control, route planning, and data acquisition. To improve the high-speed, secure communication capability and environmental adaptability of UAV swarms, this paper proposes the use of optical communication technology, which offers advantages such as rapid deployment, resistance to electromagnetic interference, and strong confidentiality, to help maintain communication links under special conditions such as emergency scenarios, strong electromagnetic interference, and communication impedance. UAVs are characterized by their high maneuverability and low payload capacity, making it difficult for traditional laser communication to maintain the communication link under such dynamic conditions. This paper proposes an optical communication scheme with a specific divergence angle, ensuring transmission distance and covering a certain communication range. The research results demonstrate that the proposed optical communication platform can maintain a transmission rate of 100 Mbps within a specified angle. We propose that the future direction of UAV optical communication development lies in more efficient transmission and reception technologies, smarter coding and modulation techniques, and enhanced environmental adaptability. Finally, we constructed two scenarios for UAV swarms, including air-to-ground and air-to-air, and assessed the application potential of swarm optical communication technologies in these two scenarios.

Region of interest (ROI) selection is a key process for remote heart rate measurement approach. Previous studies have shown that the selected ROI could easily be lost under head rotation circumstances and does not perform well under drastic changes in illumination. To solve the problems, this work proposed a novel adaptive ROI selection method. Firstly, we collected a dataset for modeling the signal-to-noise ratio (SNR) evaluated by illumination and reflection angle. Secondly, we established an SNR estimated model by studying the mathematical correlations between light intensity, reflected angle, and SNR of the regions on the face. Then, we proposed a robust ROI selection method based on SNR estimated model for adaptive ROI selection. Finally, the ROI change de-noising method is proposed to remove the ROI change noise for synthesizing the imaging Photoplethysmography (iPPG) signal and calculating the heart rate. Performances of the proposed method were tested on three datasets, including our collected dataset and two public datasets. The experimental results show that on the MR-NIRP CAR dataset, the percentage of the time that the heart rate (HR) error is less than 6 bpm (PET6) value is higher than 7.3% and 4.6%, respectively, compared with the State-of-the-art (SOTA) methods. The SNR, standard deviation error (SD), mean absolute error (MAE), and root mean squared error (RMSE) metrics are also improved on the Head-rotation and PURE datasets. Therefore, our method is robust and can potentially be applied in various scenarios.

The life ecology experimental cabinet on China Space Station is a microgravity scientific experimental platform which is suitable for plant individuals, fish, snails, fruit flies and other biological individuals as the research objects. It includes a general biological culture module (GBCM), a small general biological culture module (SGBCM), a small centrifugal experiment module (SCEM), a small controlled life ecological experiment module (SCLEEM) and a microbial online monitoring module (MOMM). The GBCM provides suitable environmental conditions for biological experiments, including temperature, humidity, light, gas concentration, visible light imaging detection, fluorescence imaging detection, program-controlled instructions, etc. The SGBCM internally provides temperature control and imaging monitoring. Other functions are realized by the replaceable culture unit. The SCEM can realize 1-2g gravity simulation in microgravity environment, and is able to support variable gravity biology research and microgravity comparison experimental research. In SCLEEM, it is planned to carry out a closed aquatic organism culture experiment with algae, fishes and snails as members. Algae provides necessary oxygen for fishes and snails through photosynthesis. MOMM is a payload used to detect the presence and classification of microorganisms in the environment. Each module works independently and has an independent electronic control system with the same architecture.This paper will introduce its basic functions, experimental conditions and expandable interface resources module by module. It provides a basis for space biologists to design experiments and a reference for payload engineers.