Search results

This paper aims to realize a fully distributed multi-UAV collision detection and avoidance based on deep reinforcement learning (DRL). To deal with the problem of low sample efficiency in DRL and speed up the training. To improve the applicability and reliability of the DRL-based approach in multi-UAV control problems.

In this paper, a fully distributed collision detection and avoidance approach for multi-UAV based on DRL is proposed. A method that integrates human experience into policy training via a human experience-based adviser is proposed. The authors propose a hybrid control method which combines the learning-based policy with traditional model-based control. Extensive experiments including simulations, real flights and comparative experiments are conducted to evaluate the performance of the approach.

A fully distributed multi-UAV collision detection and avoidance method based on DRL is realized. The reward curve shows that the training process when integrating human experience is significantly accelerated and the mean episode reward is higher than the pure DRL method. The experimental results show that the DRL method with human experience integration has a significant improvement than the pure DRL method for multi-UAV collision detection and avoidance. Moreover, the safer flight brought by the hybrid control method has also been validated.

The fully distributed architecture is suitable for large-scale unmanned aerial vehicle (UAV) swarms and real applications. The DRL method with human experience integration has significantly accelerated the training compared to the pure DRL method. The proposed hybrid control strategy makes up for the shortcomings of two-dimensional light detection and ranging and other puzzles in applications.

The purpose of this paper is to eliminate Part defects and enrich additive manufacturing of ceramics. Laser powder bed fusion (L-PBF) experiments were carried to investigate the effects of laser parameters and selective oxidation of Titanium (mixed with TiO₂) on the microstructure, surface quality and melting state of Titania. The causes of several L-PBF parts defects were thoroughly analyzed.

Laser power and scanning speed were varied within a specific range (50–125 W and 170–200 mm/s, respectively). Furthermore, varying loads of Ti (1%, 3%, 5% and 15%) were mixed with TiO₂, which was selectively oxidized with laser beam in the presence of oxygen environment.

Part defects such as cracks, pores and uneven grains growth were widely reduced in TiO₂ L-PBF specimens. Increasing the laser power and decreasing the scanning speed shown significant improvements in the surface morphology of TiO₂ ceramics. The amount of Ti material was fully melted and simultaneously changed into TiO₂ by the application of the laser beam. The selective oxidation of Ti material also improved the melting condition, microstructure and surface quality of the specimens.

TiO₂ ceramic specimens were produced through L-PBF process. Increasing the laser power and decreasing the scanning speed is an effective way to sufficiently melt the powders and reduce parts defects. Selective oxidation of Ti by a high power laser beam approach was used to improve the manufacturability of TiO₂ specimens.