# Autonomous Visual Navigation System Based on a Single Camera for Floor-Sweeping Robot
## 1 Introduction  
The huge market potential of the floor-sweeping robot has attracted the attention of researchers. The existing sweeping robots have various structures, which are generally divided into outdoor and indoor products. The outdoor type is generally a large commercial robot used to weed and clean the road [1], while the indoor type is a small household robot used to clean garbage and dust [2]. According to most studies, the sweeping robot is able to navigate and plan a path [3; 4]. In order to enable all robots in the system to safely bypass obstacles in the environment to reach the target position, obstacle avoidance control is required [5]. Vision technology has made sweeping robots develop active garbage detection and recognition, sense the environment and establish maps, plan the sweeping path, and actively avoid obstacles [6; 7]. This actually benefits from the use of industrial cameras, which are small in size, light in weight, low in energy consumption, and have a wide field of view [8; 9; 10].  
Additionally, in order to reduce costs and improve cleaning efficiency, some researchers use multiple robots for collaborative cleaning, including single-task cleaning [11; 12] and multi-task cleaning [13; 14; 15; 16; 17]. In the multi-task cleaning work, the tasks need to be scheduled and assigned to each robot in the cluster. In the process of collaborative cleaning, it is necessary to plan the motion of the robot cluster. Their motion planning strategies are divided into offline planning [11] and real-time planning [12]. Some metaheuristic algorithms are also applied in clusters [18; 19] to attain global optimization, so real-time planning is more deterministic than offline planning. Most of these sweeping robots carry out global coverage path planning in a simple environment. Even if the distributed task configuration is adopted [16; 17], most of the experiments use isomorphic robots. The high computation cost of these robots limits their work efficiency. Therefore, it is necessary to reduce the consumption of computing resources while improving the functional stability of single-robot autonomous perception, modeling, navigation, obstacle avoidance, etc.  
In order to enable the sweeping robot to work cooperatively with other full coverage light sweeping robots in the factory environment, this paper proposes a new autonomous vision navigation system of a sweeping robot based on a single-camera sensor. The system uses wireless communication and cloud computing to reduce application costs, and the key technologies in the system's application are studied, such as ground waste identification, environment awareness, and dynamic local path planning based on a depth map. Further, we carried out experiments to verify the system's performance.  
The following sections are organized as follows: in Section 2, the framework of autonomous visual navigation system is presented; in Section 3, the key technologies of the autonomous visual navigation intelligent system are studied, including garbage identification and target detection (Section 3.1), environmental depth information perception (Section 3.2), and dynamic local path planning algorithm based on superpixel segmentation (Section 3.3); experiments were conducted in Section 4, including garbage target detection experiment (Section 4.1), indoor depth perception, and dynamic local planning experiment (Section 4.2); the conclusion and outlook are given in Section 5.