The disclosed technology enables automated parking of an autonomous vehicle. An example method of performing automated parking for a vehicle comprises obtaining, from a plurality of global positioning system (GPS) devices located on or in an autonomous vehicle, a first set of location information that describes locations of multiple points on the autonomous vehicle, where the first set of location information are associated with a first position of the autonomous vehicle, determining, based on the first set of location information and a location of the parking area, a trajectory information that describes a trajectory for the autonomous vehicle to be driven from the first position of the autonomous vehicle to a parking area, and causing the autonomous vehicle to be driven along the trajectory to the parking area by causing operation of one or more devices located in the autonomous vehicle based on at least the trajectory information.

A lawn vehicle network includes a charging station having a visual identifier, a lawn vehicle having a battery, a blade system, a drive system whose output effects lawn vehicle forward movement, a processor board connected to both systems, the processor board capable of processing image data and sending commands to both systems, and a vision assembly connected to the processor board and able to transmit image data to the processor board, and the processor board, having received the image data, able to, if the image data represent a first object, maintain the drive system's output at the time of that determination, if the image data represent a second object, change the drive system's output at the time of that determination, and if the image data represent the visual identifier, maintain the drive system's output or send a shutoff command to the vision assembly at the time of that determination.

A lawn vehicle network includes a charging station having a visual identifier, a lawn vehicle having a battery, a blade system, a drive system whose output effects lawn vehicle forward movement, a processor board connected to both systems, the processor board capable of processing image data and sending commands to both systems, and a vision assembly connected to the processor board and able to transmit image data to the processor board, and the processor board, having received the image data, able to, if the image data represent a first object, maintain the drive system's output at the time of that determination, if the image data represent a second object, change the drive system's output at the time of that determination, and if the image data represent the visual identifier, maintain the drive system's output or send a shutoff command to the vision assembly at the time of that determination.

A system and method for autonomous vehicle control to minimize energy cost are disclosed. A particular embodiment includes: generating a plurality of potential routings and related vehicle motion control operations for an autonomous vehicle to cause the autonomous vehicle to transit from a current position to a desired destination; generating predicted energy consumption rates for each of the potential routings and related vehicle motion control operations using a vehicle energy consumption model; scoring each of the plurality of potential routings and related vehicle motion control operations based on the corresponding predicted energy consumption rates; selecting one of the plurality of potential routings and related vehicle motion control operations having a score within an acceptable range; and outputting a vehicle motion control output representing the selected one of the plurality of potential routings and related vehicle motion control operations.

There is provided an information processing apparatus including a controller that, when an autonomous mobile object estimates a self-position, determines which of a first estimation method using a result of sensing by a first sensor unit configured to sense internal world information in relation to the autonomous mobile object and a second estimation method using a result of sensing by a second sensor unit configured to sense external world information in relation to the autonomous mobile object is used by the autonomous mobile object based on whether a state of the autonomous mobile object is a stopped state.

Apparatus and methods for carpet drift estimation are disclosed. In certain implementations, a robotic device includes an actuator system to move the body across a surface. A first set of sensors can sense an actuation characteristic of the actuator system. For example, the first set of sensors can include odometry sensors for sensing wheel rotations of the actuator system. A second set of sensors can sense a motion characteristic of the body. The first set of sensors may be a different type of sensor than the second set of sensors. A controller can estimate carpet drift based at least on the actuation characteristic sensed by the first set of sensors and the motion characteristic sensed by the second set of sensors.

The disclosure provides an articles picking method, a control system and an articles picking system, and relates to the technical field of intelligent warehousing. The articles picking method of the present disclosure includes: receiving an order of a single articles picking point of an AGV arriving at an articles picking point, the order of the single articles picking point comprising information of articles belonging to a same articles picking point in one or more orders associated with the AGV; recommending the order of the single articles picking point to articles pickers of no less than a predetermined number; setting the order of the single articles picking point to be an assigned state to avoid the order of the single articles picking point being picked repeatedly in the event that there is an articles picker taking the order of the single articles picking point.

Systems and methods for coordinating and controlling vehicles, for example heavy trucks, to follow closely behind each other, or linking to form a platoon. In one aspect, on-board controllers in each vehicle interact with vehicular sensors to monitor and control, for example, gear ratios on vehicles. A front vehicle can shift a gear which, via a vehicle-to-vehicle communication link, can cause a rear vehicle to shift gears. To maintain a gap, vehicles may shift gears at various relative positions based on a grade of a road.

Systems and methods for coordinating and controlling vehicles, for example heavy trucks, to follow closely behind each other, or linking to form a platoon. In one aspect, on-board controllers in each vehicle interact with vehicular sensors to monitor and control, for example, gear ratios on vehicles. A front vehicle can shift a gear which, via a vehicle-to-vehicle communication link, can cause a rear vehicle to shift gears. To maintain a gap, vehicles may shift gears at various relative positions based on a grade of a road.

The present invention provides specific systems, methods and algorithms based on artificial intelligence expert system technology for determination of preferred routes of travel for electric vehicles (EVs). The systems, methods and algorithms provide such route guidance for battery-operated EVs in-route to a desired destination, but lacking sufficient battery energy to reach the destination from the current location of the EV. The systems and methods of the present invention disclose use of one or more specifically programmed computer machines with artificial intelligence expert system battery energy management and navigation route control. Such specifically programmed computer machines may be located in the EV and/or cloud-based or remote computer/data processing systems for the determination of preferred routes of travel, including intermediate stops at designated battery charging or replenishing stations. Expert system algorithms operating on combinations of expert defined parameter subsets for route selection are disclosed. Specific fuzzy logic methods are also disclosed based on defined potential route parameters with fuzzy logic determination of crisp numerical values for multiple potential routes and comparison of those crisp numerical values for selection of a particular route. Application of the present invention systems and methods to autonomous or driver-less EVs is also disclosed.