# An Efficient Task Autonomous Planning Method for Small Satellites
## 1 Introduction  
Task planning is an important part of satellite task control platform. Its main function is to solve the problem of resource utilization and task conflict in the task management of satellites, and to improve the service efficiency of the resources. In the traditional task planning, the ground stations calculate the task sequence in advance, based on the task requirements and satellite status estimation, and then upload it to the satellite for execution [1]. Therefore, the effectiveness of satellites cannot be fully realized in the current control mode, because the control instructions that satellites rely on are issued by the ground control system. Satellites cannot make a rapid response to the dynamic changes of the requirements due to the satellite-ground communication delay, time window, and other factors, which result in an inevitable waste of time and resources. Small satellites are defined as being artificial satellites with low weights and a small size, which are usually under 500 kg [2]. Small satellites have several advantages, such as simple design, short development time, low cost, easy to launch, and strong survivability. The tasks that originally needed medium and large satellites can now be executed by several small satellites. For example, OneWeb plans a mega-constellation of at least 648 small satellites to provide low-delay and high-speed Internet service [3]. However, the small satellites are limited in their computing capabilities and on-board resources, because of their low cost [4]. Existing on-board planning systems usually take a long time for planning, decision making, and execution, which do not apply to small satellites with a limited onboard computer capacity. How to realize the autonomous task planning of small satellites becomes a hot topic for researchers and the related research areas that are concerned. In this paper, we use small Earth observation satellites as an object of study in this paper. [PERSON]. [5] analyzed the feasibility of autonomous task planning of the Earth observing satellite, then proposed reaction-deliberation architecture for autonomous task planning, and designed an iterative, random greedy algorithm, but did not consider the impacts of execution on the planning. The authors of [6; 7; 8; 9; 10] deeply explored the autonomous task planning system of the Earth Observing One (EO-1) spacecraft, but the efficiency of the systems was undesirable. [PERSON]. [11] used the iterative repair method for autonomous task planning, but the state of the satellite changed in real-time, so it was difficult to grasp the time of the repair, and the duration of each plan could not be determined. [PERSON]. [12] have put forward a reverse dynamic programming method, however, the planning model is relatively simple, which is quite different from the practical projects. [PERSON] [13] established a model to solve the problem of autonomous programming for the emergency missions of agile imaging satellites, but the model has a low task completion rate when the number of general tasks is large. Other studies have analyzed the task scheduling problem from the theoretical level, developed the scheduling framework, and proposed corresponding methods, but these algorithms have shortcomings of expensive computing, which is not suitable for small satellites [14; 15; 16; 17; 18; 19]. In addition, so far, most studies only consider time-dependent constraints, while few consider the resource constraints and the dynamic characteristic of resources on the satellites [20; 21]. We also contrasted several articles on motion planning and task scheduling in robotics research and have had some enlightenment from them. [PERSON] [22] introduced a method for simultaneously planning collision-free motion and scheduling a time-optimal route along a set of given task-points based on the improved genetic algorithm, with special encoding to encounter the multiplicity of the robot inverse kinematics.