# An Orthogonal Wheel Odometer for Positioning in a Relative Coordinate System on a Floating Ground
## 1 Introduction  
Robots have been a hot topic ever since the idea of artificial intelligence was raised. The concept of \"robot\" was first mentioned in the 1920s by Czech writer [PERSON] in his novel, _Rossum's Universal Robot_[1]. Among them, the mobile robot is a kind of early development in the field of robot research. In the early 1960s, research on mobile robots was carried out abroad [2]. As the birthplace of robots [3], the United States first realized the first generation of industrial robots and put them into production, for example, Google's earliest driverless car [4], [PERSON]'s surgical robot [5], and Atlas [6], which represents the most advanced humanoid robot technology in the world. With the development of robotic research, many robot-related technologies are mature. However, for mobile robots, there are still several aspects worth studying further: First, the mobile robot full-field positioning system. Based on a certain reference position, the mobile robot can obtain the real-time position and attitude of the robot through the data measured by one or more of its own sensors when considering the changes of the environment wherethe robot is located [7]. The second is the study of path planning. In the known map environment, the mobile robot can dynamically plan a safe and reliable accurate route to reach the feasible target point according to the requirements. Finally, the motion control of mobile robot is studied. On the premise of feasible path planning for the robot, the control robot can reach the target point automatically and safely [8]. All these aspects enable the robot to complete the task. The positioning system of mobile robots is to determine the real-time pose of robots in the environment, which is the basis for the development and application of mobile robots [9]. For mobile robots, posture recognition is the foundation of path planning and motion control. High-precision sensors are needed to detect the pose of mobile robots. Therefore, how to make mobile robot pose detection in a variety of complex environment has become a problem of concern. At present, there are some mature methods for the study of plane localization: the global navigation satellite system (GNSS) [10; 11] and China's BeiDou navigation satellite system (BDS) [12], which play a major role in outdoor positioning; the pseudolite indoor positioning [13; 14] and the indoor positioning system using the beacon [15; 16] and Bluetooth [17]; in order to achieve seamless indoor and outdoor positioning services, Chinese researchers are developing a BDS/GPS indoor positioning pseudo-satellite system; precise positioning technology using real-time kinematics (RTK) [18]; using natural or artificial landmarks for positioning, such as two-dimensional code positioning [19]; signal guidance and positioning based on the sensor signals of visual camera [20], RFID [21], ultrasonic [22] and LiDAR [23]; positioning systems using Wi-Fi [24; 25] such as (OS-ELM) [26]; inertial navigation and positioning (MEMS) [27]; odometer positioning [28]; etc. When the robot is on a floating ground (such as the deck of a ship), these positioning methods may not be as effective in obtaining its own posture. When the robot is on the deck, as the ship floats along with the water, the deck is in an irregular motion in both horizontal and vertical directions. In this case, the accuracy of the robot's positioning is a challenge. For positioning methods such as GPS, GNSS and BDS, which are mainly used for outdoor positioning, signals are blocked when there are obstacles around [29]. In addition to the positioning method mentioned above, the most commonly used positioning system at present is odometer positioning using gyroscopes and orthogonal wheels; although orthogonal wheels are both adopted, the use of gyroscopes has its own limitations in the face of such floating ground. In the following article, we prove the limitations based on experiments. To solve this problem, we propose a planar positioning sensing system.