Controlling Remotely Operated Vehicles with Deterministic Artificial Intelligence

Featured Application Autonomous unmanned vehicles, deterministic artificial intelligence. Unmanned ocean vehicles can be guided and controlled autonomously or remotely, and even remote operation can be automated significantly. Classical methods use trajectory tracking errors in negative feedback. Recently published methods are proposed instead. Deterministic (non-stochastic) artificial intelligence (DAI) combines optimal learning with an asserted self awareness statement in the form of the governing mathematical model (based on physics in this instantiation) to allow control that can be alternatively adaptive (i.e., capable of reacting to changing system dynamics) or learning (i.e., able to provide information about what aspects of the system dynamics have changed). In this manuscript, deterministic artificial intelligence is applied to the heading control of a simulated remotely operated underwater vehicle (ROV). Research is presented illustrating autonomous control of a Seabotix vLBV 300 remotely operated vehicle within milli-degrees on the very first step of a shaped square wave command, and error decreased an additional sixty-two percent by the third step of the square wave command.

Automated summary

This paper presents the application of deterministic artificial intelligence to heading control of a simulated remotely operated underwater vehicle. It achieves milli-degree precision in autonomous control and reduces error by an additional 62% in different steps of a square wave command.