Skip to Content

Recreating the Feel of Water

A new approach to fluid dynamics creates virtual water that acts like the real thing.

Researchers at Hokkaido University in Sapporo, Japan, have developed a new way to recreate the feel of flowing water in two virtual-reality simulations: one for fishing and another for kayaking.

Making waves: A virtual kayaker navigates down an imaginary river (top). Instead of using a joystick, he holds a stick that connects to the ball in the center of the device (below). Wires pull on the ball to simulate the force of waves.

Most research on virtual-touch technology, also known as haptics, has focused on giving the user the sensation that he or she is feeling solid objects. But to make truly immersive virtual-reality programs, liquids will need to be simulated too, says Yoshinori Dobashi, an associate professor at Hokkaido University and a researcher involved in the fishing and kayaking simulations.

However, mimicking fluids is a difficult task. The water in a river or lake moves in intricate patterns that can only be determined using complex mathematical formulas known as Navier-Stokes equations. “To compute the accurate force, we have to solve a complex nonlinear system of equations in real time,” Dobashi says. Those numbers also have to be constantly recalculated to keep up with the ever-changing movement of the water. “The computation of the force field has to be completed and updated within 1/500 of a second,” he notes. “This is almost impossible.”

Other researchers have attempted to recreate the feel of liquids. But real-time simulations were limited to two-dimensional models of fluids, Dobashi says, because 3-D models were thought to be too processor intensive to perform in real time. He claims that his simulation is more realistic because it considers three dimensions.


  • Watch the virtual boat in action.

In order to make a 3-D system work in real time, Dobashi and his team created a model that approximates real-world forces acting on a fishing rod or kayak paddle by doing part of the math in advance of the simulation: the forces associated with different water velocities and different positions for the paddle or fishing lure were precalculated and saved in the software. Only the velocity of the water is calculated in real time, as the user moves the rod or paddle during the simulation. Once the software has determined the velocity, the associated forces are applied to the user’s hand.

To apply those forces, the fishing simulation uses a special device called the Spidar G. Created by Makoto Satoh at the Tokyo Institute of Technology’s Precision and Interface Lab, it looks much like a ping-pong ball suspended by wires. The user holds a stick that fits into the ball. As the virtual water ripples and flows, the ball and stick move to simulate the way the tip of the fishing rod would move in the real world. The virtual fisherman can control his or her fishing rod by moving the stick. An animation of the rod and lake appear on a computer screen.

The kayaking simulation requires a much larger setup, including two projection screens. Images of the water surrounding the boat are projected onto a screen on the floor, while a second screen mounted in front of the user shows what’s ahead, including rocks and bends in the river. The user holds a large rod that is roughly the length of a kayak paddle. Much like the ball in the fishing setup, this rod is suspended by motorized wires. These wires pull on the paddle to simulate the force of the water. By moving the rod against these forces, the user can steer the kayak.

Dobashi says that while there are some differences in the hardware, the basic equations used for the fishing and boating simulations are very similar. A paper outlining both projects was published in the May/June issue of the engineering journal Computer Graphics and Applications.

Bill Baxter is one of a handful of researchers who have also investigated fluid haptics. In 2004, he designed a virtual painting program as a graduate student at the University of North Carolina at Chapel Hill. Simulating a brush dipped in oil paint also involved a careful examination of fluid haptics. Having taken a ride in Dobashi’s kayak, Baxter says that the precomputation approach makes a lot of sense: it overcomes the speed limitations of today’s computer processors. “It’s also a lot of fun,” Baxter adds. But the system could still be improved, he says, to take into account more variables, such as the effects of tiny whirlpools created by spinning the paddle.

Dobashi admits that right now, the forces haven’t been calculated for every possible rod and paddle position. He hopes to fill in those blanks and create two-player games so that kayakers can race.

Keep Reading

Most Popular

This new data poisoning tool lets artists fight back against generative AI

The tool, called Nightshade, messes up training data in ways that could cause serious damage to image-generating AI models. 

The Biggest Questions: What is death?

New neuroscience is challenging our understanding of the dying process—bringing opportunities for the living.

Rogue superintelligence and merging with machines: Inside the mind of OpenAI’s chief scientist

An exclusive conversation with Ilya Sutskever on his fears for the future of AI and why they’ve made him change the focus of his life’s work.

How to fix the internet

If we want online discourse to improve, we need to move beyond the big platforms.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at with a list of newsletters you’d like to receive.