A method for controlling a subsea vehicle. The method includes receiving sensor data representing a subsea environment from one or more sensors of the subsea vehicle. The method identifies one or more objects present in the subsea environment based on the sensor data using an artificial intelligence machine. The method transmits at least a portion of the sensor data, including an identification of the one or more objects, to a user interface. The method includes receiving a requested vehicle task from the user interface. The requested vehicle task being selected by a user via the user interface. The method performs the requested vehicle task without vehicle position control from the user.

Systems and methods for controlling the motion of an autonomous are provided. In one example embodiment, a computer implemented method includes obtaining, by one or more computing devices on-board an autonomous vehicle, data associated with one or more objects that are proximate to the autonomous vehicle. The data includes a predicted path of each respective object. The method includes identifying at least one object as an object of interest based at least in part on the data associated with the object of interest. The method includes generating cost data associated with the object of interest. The method includes determining a motion plan for the autonomous vehicle based at least in part on the cost data associated with the object of interest. The method includes providing data indicative of the motion plan to one or more vehicle control systems to implement the motion plan for the autonomous vehicle.

According to the present invention, a load receiving vehicle is provided. The load receiving vehicle comprises a storage unit usable as a receiving place of a delivery article; a lock control unit capable of controlling lock and unlock of a door of the storage unit; and a communication unit, wherein if the communication unit receives delivery schedule information representing a delivery schedule to the load receiving vehicle, information based on the delivery schedule information is provided to a driver.

Vehicles and methods described herein include a vehicle that operates with a rider according to an operating parameter. The vehicle includes: a physiological monitoring sensor configured to measure a physiological parameter of the rider; an experience hybrid neural network trained on outcomes related to a rider in-vehicle experience associated with the physiological parameter to determine an emotional state of the rider; an augmented reality system configured to present augmented reality content to the rider of the vehicle based, at least in part, on the operating parameter; and an optimization hybrid neural network that identifies a variation in the operating parameter to change the emotional state of the rider and that generates a command to vary the operating parameter and the augmented reality content according to the variation.

An Improved Roadway Guidance System provides guidance elements in a roadway as means to guide a vehicle along the roadway, as well as supply important information to the vehicle to enhance the autonomous operation of the vehicle in a safe and efficient manner. The system comprises at least three parts: (1) the use of overlaid roadway emitter strips that provide an extended excitation/emission field simultaneous with direct guidance instructions to passing vehicles; (2) the use of a linearly-arranged antenna array system provided on the vehicle and adapted for interaction with the emitter strips for positionally locating the vehicle within a travel lane and providing additional informative data for operation of the vehicle; and (3) the use of a multi-port Receiver Unit that works with the antenna array and the host vehicle's guidance system to optimize autonomous operation of the vehicle.

Aspects relate to apparatus and methods for autonomously controlling vehicles at a specified location. Apparatus includes a processor configured to receive a map of a location, communicate with a plurality of vehicles at the location, and communicate with a monitor device. Communicating with the plurality of vehicles includes receiving status data from the vehicles and transmitting a waypath to the vehicles.

A method for controlling a mobile vehicle comprises the steps of selecting a control mode for autonomous driving of the mobile vehicle and transmitting information on the selected control mode to the mobile vehicle. The control mode includes a first mode and a second mode of which a restriction on a driving safety is stricter than that of the first mode. The step of selecting the control mode comprises the steps of determining whether a remote support for the mobile vehicle is required, and selecting the first mode as the control mode when it is determined that the remote support is not required whereas selecting the second mode as the control mode when it is determined that the remote support is required.

Blended operator and autonomous control in an autonomous vehicle, including: receiving sensor data from a plurality of sensors of an autonomous vehicle; determining, based on the sensor data, a degree of autonomous control for each control input of a plurality of control inputs; and applying the degree of autonomous control for each control input of the plurality of control inputs.

Systems and methods for performing high-speed geofencing in accordance with various embodiments of the invention are disclosed. One embodiment includes a robotics platform including a set of one or more motors, at least one sensor, a controller comprising a set of one or more processors, and a memory containing a controller application and a backup controller application, wherein the controller application configures the set of processors to control the robotics platform by performing the steps of receiving user commands, generating commands controlling the set of one or more motors based on the received commands. The backup controller application configures the set of processors to monitor the controller and intervene as the commands received by the controller direct the robotics platform towards a boundary by performing the steps of defining a safe set identifying positions where the robotics platform is safe, defining an invariant safe set based upon a backup set, where the invariant safe set is a subset of the safe set, and the backup set is a subset of both the invariant safe set and the safe set, receiving commands controlling the set of one or more motors to track to a desired velocity, determining if the robotic platform is approaching, and upon a determination that the robotics platform is approaching a boundary of the invariant safe set, switching control of the motors from the received commands to a combination of the received commands and backup controls generated by the backup controller application.

This disclosure provides systems and methods for controlling a vehicle by teleoperation based on a speed limiter. The method may include: receiving, at the autonomous vehicle, a teleoperation input from a teleoperation system, wherein the teleoperation input comprises a throttle control input for remotely controlling a speed of the autonomous vehicle; determining the speed of the autonomous vehicle; determining if the speed of the autonomous vehicle has reached a threshold speed below a speed limit; and upon determining that the speed of the autonomous vehicle has reached the threshold speed, reducing effect of the throttle control input from the teleoperation system such that an acceleration rate of the speed of the autonomous vehicle is reduced.