Learning-Based Multi-UAV Flocking Control With Limited Visual Field and Instinctive Repulsion

This article explores deep reinforcement learning (DRL) for the flocking control of unmanned aerial vehicle (UAV) swarms. The flocking control policy is trained using a centralized-learning-decentralized-execution (CTDE) paradigm, where a centralized critic network augmented with additional information about the entire UAV swarm is utilized...

From Short Circuit to Completed Circuit: Conductive Hydrogel Facilitating Oral Wound Healing

The primary challenges posed by oral mucosal diseases are their high incidence and the difficulty in managing symptoms. Inspired by the ability of bioelectricity to activate cells, accelerate metabolism, and enhance immunity, a conductive polyacrylamide/sodium alginate crosslinked hydrogel composite containing reduced graphene oxide (PAA-SA...

Polyacrylamide-Poly(vinyl alcohol)-Sodium Alginate-Reduced Graphene Oxide/Nylon Fabrics with Multistimuli Responses

In recent years, various functional fabrics capable of responding to multistimuli have been widely recognized as promising wearable devices. However, the obtained composite functional fabrics have only been applied in a few scenarios, rendering the achievement of multifunctional wearable application scenarios a difficult goal. Therefore,...

Learning-based resilience guarantee for multi-UAV collaborative QoS management

Unmanned and intelligent technologies are the future development trend in the business field. It is of great significance for the connotation analysis and application characterization of massive interactive data. Particularly, during major epidemics or disasters, how to provide business services safely and securely is crucial. Specifically,...

Efficient MSPSO Sampling for Object Detection and 6D Pose Estimation in 3D Scenes

The point pair feature (PPF) is widely used in industrial applications for estimating 6D poses of known objects from unrecognized point clouds. The key to the success of PPF matching is to establish correct 3D correspondences between the object and the scene, i.e., finding as many valid similar point pairs as possible. Thus, a set of...

Learning-Based Multi-Robot Formation Control With Obstacle Avoidance

Multi-robot formation control has been intensively studied in recent years. In practical applications, the multi-robot system's ability to independently change the formation to avoid collision among the robots or with obstacles is critical. In this study, a multi-robot adaptive formation control framework based on deep reinforcement learning...

New innovations in pavement materials and engineering: A review on pavement engineering research 2021

Sustainable and resilient pavement infrastructure is critical for current economic and environmental challenges. In the past 10 years, the pavement infrastructure strongly supports the rapid development of the global social economy. New theories, new methods, new technologies and new materials related to pavement engineering are emerging....

Soft sensor for ball mill load based on multi-view domain adaptation learning

In the operation process of wet ball mill, there are often multi-modal and multi-condition problems. In this paper, a multi-view based domain adaptive extreme learning machine (MVDAELM) was used to measure the mill load. Firstly, the correlation relationship between the load parameters and the two views (vibration and acoustic signals of the...

Time series forecasting based on deep extreme learning machine

Multi-layer Artificial Neural Networks (ANN) has caught widespread attention as a new method for time series forecasting due to the ability of approximating any nonlinear function. In this paper, a new local time series prediction model is established with the nearest neighbor domain theory, in which the hybrid Euclidean distance is used as...