What was described in the proposed video material reflects the urgent need for the intellectualization of automatic unmanned devices, namely the ability to independently build a route map depending on the obstacles encountered on the way. An ocean environment is a primary place where this mathematical tool for control is needed since the water column contains a number of barriers: flocks of fish, coral reefs, islands, contaminated layers, or any other obstacle to the free movement of AUVs (Massachusetts Institute of Technology, 2012). Nevertheless, such a model of energy minimization combined with optimization of travel time is also fair for any other vehicle: from the highway to outer space.
More than eight years have passed since this video was released, and during this time, humankind has made significant progress in automated technologies. Elon Mask’s drones, which have become commonplace, demonstrate the unique ability to bypass barriers on the road and in emergency areas, as is typical for AUVs. However, the machine cannot use the features of the air environment as it does submersible with currents and whirlpools. Then it is appropriate to shift attention to drones and automatic aircraft that can cut through air currents and use cyclone winds as a natural accelerator on the road. On the other hand, if drones travel in any of the geometric formations, modifying the distance between them may be an appropriate strategy for maintaining battery power. For space vehicles, such technology is also relevant, but it is worth understanding that drones in space deal with an airless environment, and the use of vortices or currents there is impossible. Still, spacecraft can use gravity distortions, wormholes, and black holes to optimize travel time or reduce battery usage.
Reference
Massachusetts Institute of Technology (MIT). (2012). Optimal paths for automated underwater vehicles (AUVs) [Video]. YouTube. Web.