Remarkable progress has been made in the high resolution, biocompatibility, durability and stretchability for the implantable brain-computer interface (BCI) in the last decades. Due to the inevitable damage of brain tissue caused by traditional rigid devices, the thin film devices are developing rapidly and attracting considerable attention, with continuous progress in flexible materials and non-silicon micro/nano fabrication methods. Therefore, it is necessary to systematically summarize the recent development of implantable thin film devices for acquiring brain information. This brief review subdivides the flexible thin film devices into the following four categories: planar, open-mesh, probe, and micro-wire layouts. In addition, an overview of the fabrication approaches is also presented. Traditional lithography and state-of-the-art processing methods are discussed for the key issue of high-resolution. Special substrates and interconnects are also highlighted with varied materials and fabrication routines. In conclusion, a discussion of the remaining obstacles and directions for future research is provided.
To overcome the limitations of the conventional artificial potential field (APF) method, which is commonly used for unmanned aerial vehicle (UAV) formation obstacle avoidance control. A novel UAV formation obstacle avoidance control method based on a light transmission model (LTM) and an improved APF method is proposed. First, inspired by the flight of bird flocks, we combine the LTM with an APF function to present an improved APF model which can help UAV find feasible free space to maneuver. From this, UAV can overcome the drawbacks of non-reachable and local minima under the action of LTM. Then, the obstacle avoidance strategy based on the fixed-wing UAV motion model is proposed, and the obstacle avoidance control algorithm for UAV formation is designed. Finally, simulation results show the effectiveness and superiority of the proposed method, which can result in a dramatic improvement in the performance of UAV formation to obstacle avoidance under the complex and non-deterministic environment.
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