The use of vibration and acoustic characteristics for micromanipulation has been prevalent in recent years. Due to high biocompatibility, non-contact operation, and relatively low cost, the micromanipulation actuated by the vibration-induced acoustic wave and streaming flow has been widely applied in the sorting, translating, rotating, and trapping of targets at the submicron and micron scales, especially particles and single cells. In this review, to facilitate subsequent research, we summarize the fundamental theories of manipulation driven by vibration-induced acoustic waves and streaming flow. These methods are divided into two types: actuated by the acoustic wave, and actuated by the steaming flow induced by vibrating geometric structures. Recently proposed representative vibroacoustic-driven micromanipulation methods are introduced and compared, and their advantages and disadvantages are summarized. Finally, prospects are presented based on our review of the recent advances and developing trends.
Wearable auxiliary devices for visually impaired people are highly attractive research topics. Although many proposed wearable navigation devices can assist visually impaired people in obstacle avoidance and navigation, these devices cannot feedback detailed information about the obstacles or help the visually impaired understand the environment. In this paper, we proposed a wearable navigation device for the visually impaired by integrating the semantic visual SLAM (Simultaneous Localization And Mapping) and the newly launched powerful mobile computing platform. This system uses an Image-Depth (RGB-D) camera based on structured light as the sensor, as the control center. We also focused on the technology that combines SLAM technology with the extraction of semantic information from the environment. It ensures that the computing platform understands the surrounding environment in real-time and can feed it back to the visually impaired in the form of voice broadcast. Finally, we tested the performance of the proposed semantic visual SLAM system on this device. The results indicate that the system can run in real-time on a wearable navigation device with sufficient accuracy.
Magnetic microrobots are vital tools for targeted therapy, drug delivery, and micromanipulation on cells in the biomedical field. In this paper, we report an automated control and path planning method of magnetic microrobots based on computer vision. Spherical microrobots can be driven in the rotating magnetic field generated by electromagnetic coils. Under microscopic visual navigation, robust target tracking is achieved using PID–based closed–loop control combined with the Kalman filter, and intelligent obstacle avoidance control can be achieved based on the dynamic window algorithm (DWA) implementation strategy. To improve the performance of magnetic microrobots in trajectory tracking and movement in complicated environments, the magnetic microrobot motion in the flow field at different velocities and different distribution obstacles was investigated. The experimental results showed that the vision-based controller had an excellent performance in a complex environment and that magnetic microrobots could be controlled to move to the target position smoothly and accurately. We envision that the proposed method is a promising opportunity for targeted drug delivery in biological research.
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