29:I[522016,["/_next/static/chunks/63b7fcc60674a395.js","/_next/static/chunks/15b411643421006b.js","/_next/static/chunks/c30851ce9d64320b.js","/_next/static/chunks/847e5fcc36806577.js","/_next/static/chunks/065d9764318d2368.js","/_next/static/chunks/f7a2a189989de24f.js","/_next/static/chunks/27a9a4c979a82611.js","/_next/static/chunks/e87f33aea3b409ff.js","/_next/static/chunks/07904650c727eea4.js","/_next/static/chunks/46256f925f164fc8.js","/_next/static/chunks/a0711c31e62236a2.js","/_next/static/chunks/eca0048b5bc78566.js","/_next/static/chunks/4bca121c9acf8666.js","/_next/static/chunks/16d56e63127d16d4.js","/_next/static/chunks/c4be71fec85bd2e7.js","/_next/static/chunks/5ab0d399186c6a49.js","/_next/static/chunks/dadfeb7a4bd24f1b.js","/_next/static/chunks/da5aa34b2c555ef9.js","/_next/static/chunks/f27222d8e2233cb0.js","/_next/static/chunks/f7eac714eb3d01d8.js","/_next/static/chunks/dfc646cc93f60815.js","/_next/static/chunks/8ed8cfa4d0ef712f.js","/_next/static/chunks/429b5c8b25956f0d.js","/_next/static/chunks/dd1804c804280679.js","/_next/static/chunks/3fe8801089f595c8.js"],""] 2a:I[523333,["/_next/static/chunks/63b7fcc60674a395.js","/_next/static/chunks/15b411643421006b.js","/_next/static/chunks/c30851ce9d64320b.js","/_next/static/chunks/847e5fcc36806577.js","/_next/static/chunks/065d9764318d2368.js","/_next/static/chunks/f7a2a189989de24f.js","/_next/static/chunks/27a9a4c979a82611.js","/_next/static/chunks/e87f33aea3b409ff.js","/_next/static/chunks/07904650c727eea4.js","/_next/static/chunks/46256f925f164fc8.js","/_next/static/chunks/a0711c31e62236a2.js","/_next/static/chunks/eca0048b5bc78566.js","/_next/static/chunks/4bca121c9acf8666.js","/_next/static/chunks/16d56e63127d16d4.js","/_next/static/chunks/c4be71fec85bd2e7.js","/_next/static/chunks/5ab0d399186c6a49.js","/_next/static/chunks/dadfeb7a4bd24f1b.js","/_next/static/chunks/da5aa34b2c555ef9.js","/_next/static/chunks/f27222d8e2233cb0.js","/_next/static/chunks/f7eac714eb3d01d8.js","/_next/static/chunks/dfc646cc93f60815.js","/_next/static/chunks/8ed8cfa4d0ef712f.js","/_next/static/chunks/429b5c8b25956f0d.js","/_next/static/chunks/dd1804c804280679.js","/_next/static/chunks/3fe8801089f595c8.js"],"CountsCommentsButton"] 2b:T51b,

Sometimes the fastest pathway from point A to point B is not a straight line: for example, if you're underwater and contending with strong and shifting currents. But figuring out the best route in such settings is a monumentally complex problem -- especially if you're trying to do it not just for one underwater vehicle, but for a swarm of them moving all at once toward separate destinations. But that's just what a team of engineers at MIT has figured out how to do, in research results to be presented in May at the annual IEEE International Conference on Robotics and Automation. The team, led by Pierre Lermusiaux, the Doherty Associate Professor in Ocean Utilization, developed a mathematical procedure that can optimize path planning for automated underwater vehicles (AUVs), even in regions with complex shorelines and strong shifting currents. The system can provide paths optimized either for the shortest travel time or for the minimum use of energy, or to maximize the collection of data that is considered most important.

Video and description courtesy of MIT