Design and evaluation of an artificial lateral line for an amphibious spherical robots

Abstract – The underwater environment is complex and diverse, and it is difficult to explore the ocean, especially in the deep sea area. The lack of light, high pressure, and lack of oxygen make it difficult for humans to work in such extreme environments. Therefore, people are beginning to hand over the burden of exploring the ocean to underwater robots. The underwater robot's perception of the underwater environment is very important for controlling the motion of the underwater robot. However, in the environment where the light is lacking at night and in the deep sea, and in the narrow space, the robot vision consisting of infrared and camera is traditionally used. The system is difficult to function, so a new sensing system is needed to assist the underwater robot in recognizing the surrounding environment. In nature, real fish use their lateral line system to sense the surrounding environment. Based on the principle of bionics, we have developed an artificial lateral line system on a bionic spherical robot. The basic principle of this artificial lateral line system is to use the pressure sensor to sense the water flow pressure around the robot when the robot swims under water, thus establishing a relationship model between the robot swimming speed and the water flow pressure to realize the relative speed of identifying the underwater robot and the water flow. Index Terms – Amphibious Spherical Robots, Artificial Lateral Line, Hydrodynamic Sensing, Speed estimation

I. INTRODUCTION

The sea area is vast and the resources are abundant. People have invested a lot of energy in ocean exploration. Due to the complexity of the marine environment, such as darkness, low temperature, and lack of oxygen, people have to hand over the task of exploring the ocean to underwater robots. Today's underwater robots are mainly divided into two types: cable-bottomed robots and cableless underwater robots[1]. Among them, cable-bottomed robots are used more and the technology is more mature, and there are many key points for cableless underwater robots. The technology needs to be solved.

There are many types and shapes of underwater robots. Spherical robots are a general term for a class of mobile robots

that are spherical in shape or nearly spherical. It installs the motion control unit, sensor, controller, power unit, etc. in the spherical shell and seals the spherical shell, which can effectively reduce the damage of the external environment to the robot parts. Spherical robots have excellent dynamic and static balance and are adaptable to harsh environments[2][3]. In addition, because the spherical outer casing receives less resistance during the movement, the energy consumption is lower, which prolongs the working time of the spherical robot[4]. Its spherical housing also has a good seal, so spherical robots also have the potential to expand into amphibious robots[5].

In order to better control the speed and attitude of the underwater robot, it is necessary to measure the flow field of the water. In the long-term evolution process, animals have great advantages in terms of motion, cognition, information processing and control compared to robots[6]. At present, there are many bionic studies, such as bionics for rats[7], and bionic robots can give robots better performance. Inspired by this, we decided to improve the ability of underwater robots to sense the environment by studying fish. In nature, fish can move freely under water because fish have a very special lateral line system that can be used to sense the flow field under water. The lateral line system is actually an important sensory organ for fish and amphibians. It can sense the changes of water flow pressure, low frequency vibration, temperature change, etc. in the surrounding environment through the sensor located in the lateral line. This is very important for fish to find bait, find enemy, and avoid obstacles. The lateral line system of fish is usually distributed symmetrically on both sides of the fish, mainly on the head. Based on the discovery of the surface of the fish, the lateral line is a fluid sensor of a spatially distributed system consisting of a series of mechanical sensing units called the neural mound[8], which can be divided into two categories: the surface nerve mound and the lateral tube nerve mound[9]. The surface nerve hill is located in the superficial surface of the skin and consists of a series of hair cells that are sensitive to flow velocity and are called displacement sensors. When the water flow moves

Yao Hu1, 2, Huiming Xing1, 2, Liwei Shi1, 2*, Shuxiang Guo1, 2, 3*, Xihuan Hou1, 2, He Yin1, 2, Yu Liu1, 2

Debin Xia1, 2, Zan Li1,2, Mugen Zhou1, 2 1 Key Laboratory of Convergence Medical Engineering System and Healthcare Technology, the Ministry of Industry and

Information Technology, School of Life Science, Beijing Institute of Technology, No.5, Zhongguancun South Street, Haidian District, Beijing 100081, China

2 Key Laboratory of Biomimetic Robots and Systems, Ministry of Education, Beijing Institute of Technology, No.5, Zhongguancun South Street, Haidian District, Beijing 100081, China

3 Faculty of Engineering, Kagawa University, 2217-20 Hayashi-cho, Takamatsu, Kagawa, Japan E-mails: huyao@bit.edu.cn; shiliwei@bit.edu.cn; guoshuxiang@bit.edu.cn;

* Corresponding author

relative to the fish, the hair cells located on the surface of the fish body are inclined. If the hair cells are turned to the side of the cilia, the cells are stimulated, and if the hair cells fall to the side of the stereocilia, the cells inhibit the stimulation[10][11]. The lateral tube nerve hill is located in the lateral line below the epidermis and is connected to the outside through the small hole. Generally speaking, there will be a lateral tube nerve nucleus between the two small holes. The difference between the small holes will cause the flow of mucus in the lateral line tube, thereby stimulating the lateral tube nerve nucleus[12]. Therefore, the lateral tube nerve nucleus can sense the pressure difference between the small holes. Therefore, the lateral tube nerve hill is also called an acceleration sensor. The response of the surface neural crest to DC and low frequency components is proportional to the net velocity. The lateral tube nerve hill responds to high frequency components and reacts in proportion to the net acceleration[13][14].

Inspired by this, this paper simulates the relationship between water flow pressure and fish swimming speed by installing a pressure sensor on the spherical shell of a spherical robot to simulate the lateral line sensor of real fish, and realizes the recognition of the swimming speed of the robot. At the same time, the effects of water depth on the previously established relationship model are studied when the robot is at different depths under water, and the model is optimized and improved. The designed artificial lateral line system is used to realize the perception of the underwater environment, thus helping the robot to avoid obstacles and plan the navigation route.

II. AMPHIBIOUS SPHERICAL ROBOT

In order to improve the flexibility and dynamic performance under water, we proposed a pint-sized spherical amphibian robot. The spherical robot is a cableless underwater robot, which is powered by a battery pack and has strong autonomy and flexibility. Its mechanical structure is shown in the figure 1. The spherical robot is divided into upper hemisphere and lower hemisphere. The upper hemisphere consists of two cabins, a sealed cabin and a water cabin. The sealed cabin is equipped with a CPU and control circuit for planning the motion path and controlling the attitude of robot. The water cabin is used for balance the gravity and buoyancy of the robot under water, so that the robot can be suspended under water. The upper hemisphere also contains 12 pressure sensors for detecting the pressure under water. A binocular camera is installed on the water cabin to identify and tracking the target[15][16]. A sonar communication module is installed on the top of the upper hemisphere to receive control commands from the water surface and transmit various data of the robot.

The lower hemisphere is equipped with a battery compartment and four legs. The four legs are evenly distributed under the robot. Each leg has 3 movable joints, each of which is driven by a servo motor[17]. A water jet motor is mounted on the last joint. When the robot is walking on land, the water jet motor can provide support to the robot. When the robot swims under water, the water jet motor can power the robot.

(a) (b)

(c)

Fig 1. Structure of the amphibious spherical robot. (a) Front view. (b) Vertical view. (c) Details of mechanical structure.

III. ARTIFICIAL LATERAL LINE SYSTEM

The lateral line system of a robotic fish is a sensor system consisting of a series of sensors mounted around the body of a robotic fish[18]. This sensor system can simulate the lateral line system of real fish, obtain the water flow pressure data around the body of the robot fish, and analysis the pressure data to realize the recognition and adjustment of the movement state of the robot fish[19].

Fig 2. Pressure sensor profile. The 12 pressure sensors are evenly distributed

around the robot, the angle between two adjacent pressure sensors is 30°.

In nature, the body evolved into a streamlined shape in order to reduce the resistance generated by movement under water[20]. This streamlined shape causes the lateral line sensors to vary in the number of different parts of the body of the fish. In general, the lateral line sensor has a large difference in the distribution and number of strokes in different parts of the fish's unilateral body, but is symmetrically distributed on both sides of the body. Different types of fish have different lateral line tissues, such as the number, location and distribution of body

surface neural mounds, lateral tube nerve hills and lateral tube small holes[21]. In addition, fish prefer turbulent water flows, while fish inhabiting lakes tend to be less turbulent. The lateral line systems of these two fish species vary widely, which is the effect of different living environments on the lateral line structure. When we are designing a lateral line system, we need to consider the environment in which the robotic fish work. Different working environments may require different lateral line systems. The lateral line system we designed uses 12 pressure sensors. The 12 pressure sensors are symmetrically and evenly distributed. The angle between two adjacent pressure sensors is 30°, and 12 pressure sensors are mounted on the side of the robot.

IV. EXPERIMENT

A. Experiment environments

The experiment was carried out in a pool of 170 cm long, 250 cm wide and 100 cm deep. The maximum water depth of the pool was 0.67 m. In order to ensure that the robot can move at a constant height and constant speed under water, a mechanical system that can pull the robot is designed. The whole mechanical system consists of two parts. The first part is mainly composed of stepper motor, stepper motor controller, stepper motor driver, power supply, etc. The main function of this part is to generate the force that enables the robot to move forward at a constant speed. The second part consists mainly of various component, which are assembled into a mechanical shelf that connects the motor and robot together and provides a platform for carrying the robot.

(a) (b)

Fig 3. Experimental device. It can keep the robot moving at a uniform speed. (a) Mechanical structure of experimental device designed in

SolidWorks. (b) Experimental device.

Considering that the underwater robot's movement speed under water is generally not too fast, the robot's motion speed designed in this experiment is at least 0.1m/s, the maximum is 0.5m/s, and the increment is 0.05m/s, the number of the experiments is 9. In order to ensure the accuracy of the experiment as much as possible and reduce the accidental error, each group of experiments was repeated five times and finally averaged. The speed of the robot is precisely controlled by the stepper motor.

Fig 4. Robot moves in the direction of P1. Because the flow direction

around each pressure sensor is different, the data of each pressure sensor is different.

B. Experimental results and analysis

We analyzed the results of a total of 9 experiments in a series of speed experiments at a speed of 0.1 m/s to 0.5 m/s with a gradient of 0.05 m/s.

Fig 5. Pressure data at a speed of 0.1 m/s to 0.5 m/s with a gradient of

0.05 m/s.

By analyzing the data, and taking into account the impact of experimental errors and the pool water fluctuations on the experiment, we found that the pressure of the water flow around the robot body becomes larger as the robot swims faster. By analyzing the data, we found that the pressure data received by the sensor has a small variation range, and the pressure data obtained by the sensors P1, P2 and P12 have a good linear relationship with the swimming speed of the robot. This is because the pressure sensors P1, P2 and P12 are located right in front of the robot, and the water flow pressure is large, the obtained experimental data has a good linear relationship with the water flow pressure. While the spherical robot moves under water, the size of the robot is large, which will cause the

turbulence of the water flow. Therefore, when the robot moves forward, the turbulence of the water flow is larger at a position far from the center of the robot motion, and therefore, the influence of the speed on the pressure is smaller. In the second half of the robot's body, the turbulence of the water flow is even greater. The turbulence of the water flow has a greater impact on the experimental results, and the effect of the speed is even smaller, so it is difficult for us to find out the relationship between speed and pressure by analyzing the pressure of other sensors.

Since the pressure sensor P1 is located directly in front of the robot motion, it is possible to measure the pressure change of the robot during movement very accurately. Therefore, we perform a quadratic polynomial fit on the data of the pressure sensor P1. In order to eliminate the influence of the depth change on the pressure sensor, before the data is fitted, the pressure sensor P1 data is subtracted from the robot's static pressure, and then the data is fitted. The fitting results are as follows:

2668.1 98.93 12.39P V V= ∗ − ∗ +

Fig 6. The fitting results of pressure sensor P1

By comparing the differences between the different pressure sensing data at the same speed, we found that when the robot moves forward at a certain depth under water, the pressure of the water felt by the 12 sensors of the robot is different. It can be seen from the figure that the pressure change of the P1 sensor is the largest, that is, the difference between the hydrostatic pressure and the hydrodynamic pressure is the largest. The rest of the sensor pressure changes with the P7 sensor as the center of symmetry, showing a symmetrical change. An analysis of the positional changes of the sensors when the robot moves under water reveals that this is closely related to the completely symmetrical shape of the spherical robot. Sensors P1 and P7 are located on the central axis of the robot. Because the sensor P1 is located in front of the direction of motion of the robot, the pressure changes the most, which best reflects the relationship between pressure and speed. The sensor P7 is behind the direction of the robot movement. At the rear, there may be vortices, and the influence of the water flow disturbance is large, resulting in the pressure of the P7 sensor not having a good linear relationship, and the pressure changes little, and the values are relatively concentrated. The symmetrical shape of the

spherical robot is basically symmetrical when the water flows under water, and the remaining sensors are symmetrically distributed. Therefore, the rest of the sensor pressure changes are basically symmetrical. Because of the unique pressure changes of the P1 and P7 sensors and the symmetry distribution of the rest of the sensor pressure changes, we can judge the moving direction of the robot by analyzing the pressure changes of the sensors during the movement of the spherical robot.

Fig 7. Data differences between different pressure sensors at a specific speed.

V. CONCLUSION

In this paper, we designed a pressure sensor-based artificial lateral line system for spherical amphibious robots. The artificial lateral line system consists of 12 pressure sensors distributed around a spherical amphibious robot. Through practical experiments, we found that the pressure sensor data is highly correlated with the velocity of the spherical amphibious robot relative to the water flow, and through the quadratic polynomial fitting of the data, the mathematical relationship between the pressure sensor data and the velocity is found. Therefore, the artificial lateral line system can be used to measure the water flow velocity around the spherical amphibious robot for the hydrodynamic sensing of the spherical amphibious robot under water.

ACKNOWLEDGMENT

This work was supported by National Natural Science Foundation of China (61773064, 61503028). This research project was also partly supported by National High Tech. Research and Development Program of China (No. 2015AA043202).

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