Have you ever imagined that you could swim with robotic fish someday? This may happen in the near future. More surprisingly, these robots would be capable of monitoring the aquatic quality around you and may even save you when you are drowning. These scenes have happened a couple of times in my dreams. I am Jianxun Wang, a Ph.D student of Prof. Xiaobo Tan in the Smart Microsystems Lab at Michigan State University, and I have been working on robotic fish for more than two years.
Back when I was a senior in college in China three years ago, I already knew that I would be working with a fantastic group on the research of robotic fish. I could still remember every detail the first time I came into our lab in the Fall of 2009. John Thon, a passionate researcher in our lab as well as a teacher at Holt Junior High School, gave me a warm welcome and guided me through the existing work. Our research began with an outreach activity to stimulate interest of precollege students in the fields of science and engineering through demonstrations of fish-like robots. These robots soon turned into a much more serious set of scientific projects. Later that day, Michael Carpenter, an undergrad research assistant, and Freddie Alequin, a graduate research assistant, showed me a demo of the robotic fish working in a 15-foot-long tank holding 6,000 gallons of water in the Smart Microsystems Laboratory. This is the first time I saw a real robotic fish prototype – a shell of green plastic with a rigid tail capable of swimming straight and making simple turns. I promised myself that I could and would make substantial contributions to propel these projects forward. From then on, I have been working with John, Freddie and Cody Thon, an optimistic and accommodating undergrad research assistant, all of whom are now my close friends.
One year later, we developed a 6-inch fishlike robot with gray and yellow stripes modeled after a panfish. It had a GPS unit mounted on its head, a 3D compass embedded inside the front of the body, a wireless communication component on top of the shell, and a dissolved oxygen sensor suspended from its bottom. This robotic fish was designed to patrol a pond or a lake, while collecting and sending data about water temperature and the dissolved oxygen level. The robotic fish will provide a level of spatial and temporal sensing resolution that traditional water quality measurement approaches cannot match. Thanks to Felix Adisaputra, an undergrad research assistant working with me, we had a user friendly Graphical User Interface with Labview for remotely operating the robotic fish.
At nearly the same time, I started to shift part of my research time to work on the modeling of robotic fish. The main focus of my contributions are the control of individual and groups of them. The mathematical model I developed is currently being used for evolutionary design of robotic fish, which is a collaboration with Prof. Philip McKinley’s group. There, I met Tony Clark, a smart and hardworking Ph.D student of Prof. McKinley. We work together on the challenges existing in the development of autonomous robotic fish, which include realizing high maneuverability and high energy efficiency at the individual robot level and achieving adaptive coordinated movement (such as schooling) at the group level. Live fish and evolution computation provide a source of inspiration for effectively addressing these challenges. Consequently, in this project, Liliana Lettieri and Jason Keagy (two knowledgeable research associates from Prof. Jenny Boughman’s group) and Tony and myself are working together to create autonomous robotic fish by merging bio-inspiration, evolutionary design, and experimental prototyping. In particular, Tony has shown that the dynamic models I developed for robotic fish can be used successfully in evolving waypoint-following control strategies for these robots.
Recently, Osama En-Nasr, an excellent undergrad research assistant, John, Cody and I have been developing a so-called “predator robotic fish”, which will be used to study cooperation and social behavior in stickleback fish in collaboration with Prof. Boughman’s group. The idea is to use the robotic fish as a predator to elicit animal responses, since this “predator fish” could be controlled to demonstrate many complicated and repeatable behaviors. In this prototype, I have to acknowledge a very important and impressive technique: 3D printing. Supported by an NSF grant called “Evolution Park,” we luckily have this football table size 3D printer. With 3D drawing and selection of material, this 3D printer can provide us with arbitrary three-dimensional objects that have varying stiffness within a same object, which makes it much easier to create robotic fish prototypes. In the near future, we will print different types of robotic fish just like real fish. From this semester, we have two new members joining in this special group, Jared Moore and Sanaz Behbahani, and I am sure we can make some fascinating advances in the area of robotic fish with their contributions.