September 2020 OES Beacon

Research and Education Activities under the Coronavirus Pandemic

Takumi Matsuda, Meiji University, IEEE OES Japan Chapter, BEACON Associate Editor

  1. Introduction
Figure 1 Deployment scene of 3 AUVs in the sea experiments.

I have been studying the navigation methods of the multiple autonomous underwater vehicles (AUVs) for ocean surveying such as seafloor mapping or environmental monitoring. It is essential for the AUVs to cooperate with each other to realize efficient surveying. In underwater environments, there are more restrictions than on land because sound waves, which have narrow bands, are used for positioning and communication among the AUVs instead of radio waves. To overcome this problem, I have studied cooperation algorithms among the AUVs. I recently studied a navigation method of multiple AUVs in which one AUV serves as a survey leader (parent AUV) and the other AUVs (child AUVs) build a wireless positioning and communication network centered on the parent AUV [1]. Since the parent AUV has high positioning performance and navigational capability, other child AUVs can achieve accurate surveying through the parent-centered network. Sea experiments were conducted with 3 AUVs last year. Figure 1 shows the deployment scene of 3 AUVs.

From this April, I moved to Meiji University from the University of Tokyo, and have been studying with Professor Yoji Kuroda while applying the idea of parent-child robots to land robots to develop security technology by robots for airports, stations and other environments.

  1. Research and Education Activities under the Coronavirus Pandemic
Figure 2 Robot simulation in the environment with both static obstacles and moving pedestrians using Gazebo [3].
Due to the coronavirus pandemic, research and lectures are being conducted online in Meiji University. Research in robotics is also conducted mainly based on simulators. Particularly, the middleware called ROS (robot operating system) has been used widespread. ROS makes it possible to simulate algorithms using data close to actual one. It is also possible to model the real environment and to simulate robot processing with Gazebo, which is a virtual simulator of a 3D model for a robot and an environment [2]. Figure 2 shows the example of the robot simulation using Gazebo [3].

Regarding the lecture, I am in charge of the experimental lecture, which involves controlling a motor. It is difficult to conduct such an experiment online. Thus, a simulation model to control a motor was developed using MATLAB and Simulink, which are software products developed by MathWorks (Figure 3) [4]. The model can output the result of the motor rotation speed according to the time transition for each student (Figure 4). Since each student has different results, they can face the data with a fresh mind. The purpose of this experiment was to allow students to think freely based on the results even if online. As a result, various discussions were obtained from the students. In addition, by utilizing the simulation and taking the advantages of software, it was possible to perform the experiment under various conditions that are difficult to prepare with actual objects.

Students were surveyed about the experiment. Following are some answers from the students:

  • It was able to analyze and discuss the data carefully, even in the online experiment.
  • It was able to understand the relationship between the contents of the experiment and the products.

On the other hand, there were some answers that pointed out the improvements:

  • I wanted to collaborate with other students to conduct the experiment.
  • It was unfortunate that I could not experiment with the real machine.

From the answers, I believe that the purpose of the experiment, which is for students to analyze and discuss the data, has been achieved. However, I think that improvements are also necessary. Although it is difficult for all students to experiment with real machines online, I think it is necessary to make an experimental environment in which students can experience the movement of the machine through simulation. The experiment was conducted individually in this time, but I would like to consider an online experiment, which includes the perspective of group work.

Figure 3 A simulation model for the motor control using MATLAB and Simulink. The above model can simulate the step response of the motor. The below model can simulate the motor response by adding the PID controller.
Figure 4 Simulation results for the motor control. The blue line shows the result of the step response of the motor. The red line shows the response by adding a PID controller.
  1. Conclusion

Due to the coronavirus pandemic, research and education activities in my university are conducted mainly online. Although it has become inconvenient in some aspects, the value of various existing tools is being re-evaluated and new tools are also being born. I think that this change in lifestyle will lead to the creation of new technology. Robots and virtual technology will also be becoming important. Thus, I believe that, in addition to unmanned automation technology by robots, fundamental technology that supports from development to practical use of robots online and virtually will generate new value in the future.

Figure 5 The author’s photo taken together with AUV Tri-TON.

Figure 5 shows the author’s photo taken together with AUV Tri-TON.

For more details about the activity of Meiji University and Autonomous Mobile Systems Laboratory (Kuroda Laboratory), visit the links shown in the references [5] and [6].



  • Matsuda, T. Maki, and T. Sakamaki, “Accurate and efficient seafloor observations with multiple autonomous underwater vehicles: theory and experiments in a hydrothermal vent field,” IEEE Robotics and Automation Letters, vol.4, no.3, pp.2333–2339, 2019.
  • Gazebo,
  • Fan, X. Cheng, J. Pan, P. Long, W. Liu, R. Yang, and D. Manocha, “Getting robots unfrozen and unlost in dense pedestrian crowds,” IEEE Robotics and Automation Letters, vol.4, no.2, pp.1178–1185, 2019.
  • MathWorks,
  • Meiji University,
  • Autonomous Mobile Systems Laboratory

Kuroda Laboratory,