Underwater robots aren’t new, but only a few are efficient at their jobs. They need to be agile, fast, and must swim like real fish. While that has also been tried, replicating a fish that swim faster or slower is something that hasn’t been done yet.
Marine biologists already know that changing the rigidity of the tails can help them overcome the hurdle. However, the problem is that it’s difficult to measure that while a fish is swimming. Now, with the help of a combination of fluid dynamics and biomechanics, scientists from the University of Virginia have derived a formula that enables the robot with a specifically designed tail that is as good as a natural tail.
Robot swimming like a fish
When they applied the formula to a tuna-shaped robot, they learned that it could swim at a greater variety of speeds using almost half as much energy when compared to the one with a fixed tail.
“Having one tail stiffness is like having one gear ratio on a bike,” Dan Quinn, one of the co-authors of the study, told Big Think. “You’d only be efficient at one speed. It would be like biking through San Francisco with a fixed-gear bike; you’d be exhausted after just a few blocks.”
With a tuna-like robot, the team plans to scale their tail technology for use on both smaller and bigger machines. The researchers are also developing one that undulates like a stingray. Their work could help in building more efficient underwater drones.
New age of underwater drones?
The new drones will be able to travel quickly through deep water to a remote location and then slow down to investigate an area. Their invention could also be used by the Navy to inspect their ships for damage.
Recently, students from Oregon State University developed a bipedal robot that uses machine learning to teach itself how to finish a 5K racecourse, the school announced. The robot named Cassie ran 5 km of gravel, sidewalk, and fields to finish a course on a single charge in 53 minutes. The Defense Advanced Research Projects Agency has funded $1 million for the research.
