# Research on the Cleaning Method of Unmanned Sweeper Based on Target Distribution Situation Analysis
## 2 Related Works
### Research on Path Planning of Unmanned Sweepers  
Path planning technology is one of the core elements of the research on sweeping robots, and the so-called robot path planning technology works by the robot planning a safe route by itself based on its own sensors' perception of the environment, while efficiently completing the operational tasks [14]. The path planning of mobile robots can be divided into two types according to their purpose--one is full-coverage path planning (CPP) and the other is traditional point-to-point path planning. Full-coverage path planning has been extensively studied by several authors. [PERSON] et al. [15] considered that full-coverage path planning is related to the covering salesman problem and studied in detail the advantages and disadvantages of several CPP algorithms. [PERSON] [16] reviews the principles of CPP, creatively discusses the use of deep reinforcement learning methods to solve the CPP problem and discusses its development trends, and the authors argue that coverage algorithms can be divided into classical and heuristic-based algorithms, depending on the a priori knowledge of the environment surrounding the on-board sensors. Point-to-point path planning is more like the well-known traveling salesman problem (TSP), [PERSON] et al. [17] detailed the state-of-the-art path planning in automation, robotics and video games, respectively, A star and its variants [18], RRT algorithm [19], artificial potential field method [20], etc.  
The traditional sweeping robot's operation task is to clean the room, so its path planning belongs to fully traversing path planning, and it needs to satisfy the traversability and non-repetitiveness. [PERSON] et al. [21] designed an inward spiral traversal method and proposed a shortest path out of a dead zone scheme based on the A star algorithm to avoid the problem of inward spiral traversal of the sweeping robot into the dead zone. [PERSON] et al. [22] considered the global planning of cell paths for inter-cell transfer by exhaustive search and the ant colony algorithm, so that the sweeping robot can work better in complex environments. As for what needs to be accomplished in this task, the path planning in which the unmanned sweeper will pass all the garbage from the starting point to the end point belongs to the traditional point-to-point path planning. Path optimality is related to the shortest cover path or TSP, which is usually the planning of a path with minimum travel cost to visit all points that pass through multiple images containing garbage. The new path planning problem explored here can be called the TSP-CPP problem, considered as an integration of the TSP and CPP problems [23]. The multiple-TSP problem was explored by [PERSON] et al. [24], and [PERSON] et al. [25] provided a mixed-integer planning formulation for this new problem, and then developed a dynamic-based approach based on a CPP method covering a single convex polygon region planning exact method that finds the optimal path, in addition to proposing a heuristic method that can generate high-quality plans very efficiently.