Beihang University

Dapeng Wu

Peng Yang

Xianbin Cao

Xing Xi

Wenbo Du

Zhenyu Xiao

Chao Yin

Provided is a multi-UAV continuous movement control method for energy efficient communication coverage. The method includes: determining observation information at a current moment, the observation information including one or more of the following: energy consumption information of a UAV, coverage indication information of users covered by a UAV network facilitated by the UAV or coverage fairness information of the UAV network; determining control information corresponding to the observation information using a DDPG model according to the observation information, wherein the DDPG model is generated from a DDPG algorithm with sample information as an input, the sample information indicating a mapping relationship between sampled observation information and sampled control information; and controlling the UAV to move according to the control information. The value of the mobile policy from the DDPG model is continuous, thus mitigating the imprecision in existing movement control due to the discreteness in evaluating the mobile policy.

Multi-UAV continuous movement control method, apparatus, device, and storage medium for energy efficient communication coverage

Provided are a network selection method and an apparatus for integrated cellular and drone-cell networks, where the method includes: acquiring a dynamic network model and a dynamic user model, generating a random event vector according to the dynamic network model and the dynamic user model; generating an action vector according to the random event vector; obtaining an individual utility of each user according to the action vector and the random event vector; constructing a first selection model; obtaining the value of the action probability according the first selection model to determine networks that the users choose to access according to the value of the action probability.

Network selection method and apparatus for integrated cellular and drone-cell networks

A joint search method for UAV multiobjective path planning in an urban low altitude environment first constructs a static safety index map based on static known obstacles. Meanwhile, based on proactively detected obstacles that are not marked on a geographic map by a UAV, the method constructs online a dynamic safety index map. Second, a multiobjective path planning problem is solved using a joint offline and online search method. Moreover, this method first plans offline the least cost path from a starting point to an end point and then invokes the online search scheme to replan online a changed path when the UAV detects unknown obstacles. Thus, the UAV can avoid dynamic obstacles effectively. The online search scheme has a small search space and can quickly replan a safe path for the UAV, thus satisfying the requirement of UAV on the real-time path planning.

Growing community of inventors

Beijing, China

Dapeng Wu