Distributed UAV swarm based on spatial grid model

2020-11-26 14:53BangkuiFANZhiweiZHANGRuiyuZHANG
CHINESE JOURNAL OF AERONAUTICS 2020年11期

Bangkui FAN, Zhiwei ZHANG, Ruiyu ZHANG

a Beijing Institute of Information Technology, Beijing 100094, China

b Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

c School of Electronics, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China

d National Key Laboratory of Microwave Imaging Technology, Beijing 100090, China

KEYWORDS

Abstract Unmanned Aerial Vehicle (UAV) swarm has become the inevitable trend of development, which will enjoy broad prospects to be applied in the future. However, the change of UAV application mode will certainly bring new technical challenges in the flight management,environmental perception,collaborative control as well as other fields. This paper considers that it can be an effective solution to realize the unified management of spatial information on the UAV platform by adopting the spatial grid model represented by the GeoSOT-3D, and to reduce the workload of flight management, airborne environmental perception, and ranging in the neighborhood through the association and query of all spatial grid data.

1. Introduction

With the advent of the post-information era,information technology represented by ‘‘cloud computing, Internet of Things,big data, mobile Internet, artificial intelligence” has created favorable conditions for the development of intelligent UAV swarm technology.1Compared with the performance of a single UAV,the intelligent UAV swarm helps effectively enhance the task execution capability of the system.2However, the coexistence of large-scale UAVs will also give rise to some new challenges:In terms of flight management,the flight space planning of existing UAV swarm is usually represented by a series of floating-point coordinates, but as the number of UAVs increases and the running space becomes complicated,the outer boundary and internal environment of the airspace become more complex.The floating-point coordinates method will be difficult to describe the complex airspace environment.In terms of environment perception, when the UAV swarm is flying in low-altitude or urban areas, the traditional technology faces the following three problems:First,the environment is complex,and the data types are numerous.It is necessary for the UAVs to equip with a large number of sensors for fusion sensing, and the calculation amount is large. Second, in the process of environmental perception,the UAVs are susceptible to wind, light and magnetic field. The airborne sensor data may carry a lot of noise.Third,because of the lack of environmental data sharing, the same static obstacle is easily detected by the UAVs for many times, increasing the workload of the system. In terms of collaborative control, the distributed swarm control of UAV usually relies on the distance between neighboring individuals. Although accurate distance information can be obtained based on the latitude and longitude floating-point arithmetic method, as the number of individuals in the UAV swarm increases, the calculations of single aircraft will increase on a large scale. The inadequacies of floating-point coordinate computing methods will gradually appear.

The digitization of running space is a solution to solve the technical challenges in the large-scale swarm of UAVs. The idea is to rely on the global spatial subdivision framework to discretize the space into multiple grids of multiple levels, so that each grid has unique,hierarchical,and coded expressions.The input and association of multi-source information attributes in the running space allow each grid to have multiple attributes and use this as the basic unit of the digitized space.Thus, the spatial grid model can be used to realize the digital representation of the flight space of the UAV swarm, the pre-storage of environmental information, and the efficient query of spatial attributes.

2. Spatial grid model

The research on the theory of spatial information subdivision organization has made a lot of achievements, but most of which are still limited to the surface of the Earth,and it is difficult to reflect the multidimensional characteristics of the UAV platform. At the same time, most of 3D grid models are limited to a specific professional application field or limited to local areas, so the global grids’ multi-source geographic information management lacks consistency.3

2.1. GeoSOT-3D grid model

GeoSOT-3D grid is a typical spatial grid model that can serve UAV swarm technology. By expanding the Earth through three iterations and continuously subdividing it, it can possess global multidimensional octree hierarchical characteristics.4This framework can divide the surface of the Earth into a series of multi-level and multi-scale spatial grids(from 100 km to centimeter-level). At the same time, the height dimension is introduced on the basis of the two-dimensional grid, covering the Earth space up to 500000 km and down to the center of the Earth. Based on the GeoSOT-3D grid division, hierarchical codes are assigned to each grid according to the spatial ‘‘Z”order,achieving a global unified index.Multi-source heterogeneous data in the UAVs’ running space is converted to a uniform format, and spatial entity object data is converted into spatial grid attributes. Using the characteristics of the spatial grid with unique coding identifiers, the attributes of each discretized grid space are correlated with the code, and all the spatial information is incorporated into the unified index table.Finally, we can use index tables to implement the representation of spatial information.

2.2. Characteristics

The characteristics of the spatial grid model represented by the GeoSOT-3D can be summarized as follows:

Be able to carry: The spatial grid model is a unified framework for organizing static spatial entity data. Split grid elements can cover the whole earth space seamlessly and stacklessly. Spatial geographic information is recorded in the form of a spatial grid.

(1) Be able to match.Any object in space can be aggregated from one or more split grids. All objects and attributes in static space can be indexed by grid codes for fast queries and matching.

(2) Be able to locate. The spatial grid code corresponds to latitude, longitude, and altitude separately, which can rapidly convert location information and the grid coding to each other.

(3) Be able to compute. The spatial grid code can convert the longitude, latitude,and altitude of the grid into binary one-dimensional integer code and simplify the threedimensional space ranging task by making comparisons between the grid codes.

3. Future prospect

The spatial grid model can be combined with the UAV swarm technology in terms of flight management, environment perception, and collaborative control.

In the aspect of UAV swarm flight management,the spatial grid is the basic unit of the digital operating space,which provides an efficient spatial expression for swarm flight management and control. Before the mission, the managers can set the UAV’s running airspace according to the mission location and flight route in advance.The spatial grid model manages to describe the running space in the form of the digital grid efficiently, and record the information of flight management in the form of grid attributes in the corresponding space unit.Based on this process,the airspace restrictions for UAV swarm can be realized, and a basic map is provided for planning the route of UAV swarm.

In the aspect of UAV swarm environment perception, spatial grid model is the unified framework of spatial information management, which provides all-round static environment information in the running space for the system. Under the framework of the spatial grid model, UAV saves the static environment information index table of running space beforehand and obtains the spatial location of the static environment by querying the index table. Airborne equipment is mainly responsible for perceiving and processing dynamic environment entities, which can effectively reduce the task of UAV onboard sensing and reduce the number of airborne sensors for environment perception. All these provide efficient information support for UAV swarm decision-making.

In the aspect of UAV swarm collaborative control,the spatial grid is the bearing unit of spatial attributes,which provides efficient data for collaborative interaction between individuals.5The self-organizing swarm control of UAV usually relies on the distance between neighboring individuals. In space distance measurement, the spatial grid model can transform the traditional floating-point operation based on longitude, latitude and altitude coordinate into spatial distance query under the spatial attributes of the grid.That is to say,the spatial distance between the grid and its neighborhood grid is stored first as the grid attributes in the index table, in which grid code serves as the primary key, and the spatial distance of the two UAVs in the neighborhood can be queried through the coding information. This method can support the formation of largescale swarm behavior and meet the intrinsic needs of ranging in neighborhood and collision avoidance during swarm flight.

4. Conclusions

The space grid-based UAV management and control method,which uses the architecture of the grid model to store spatiotemporal geographic information data on each UAV platform,realizes the use of increased storage space in exchange for airborne computing reduction. This method has the characteristics of convenient space-time expression and low on-board computation.

The spatial grid model helps efficiently digitalize the flight space and store the static environment data on the UAV platform. The UAVs can obtain some geographic information by reading the on-board geographic information data, which can greatly reduce the workload of airborne equipment’s real-time perception of the surrounding environment and no-fly zone,and provide support for the UAVs’path planning.Meanwhile,with the assistance of this framework, the distance measurement between individuals in the swarm can be transformed into a high-efficient optimized query, thus reducing the computing time to a large extent.In addition,based on the spatial grid model,time can also be subdivided,and time information is used as a spatio-temporal attribute. Thus, unified management of spatial dynamic environment information can be implemented in a network environment. The spatial grid model provides a new perspective on the realization of UAV swarm, and it has great advantages in flight control, environment perception, collaborative control and so on. Therefore,it can be predicted that the spatial grid model will become one of the study areas of UAV swarm.