A vehicle configured to operate in an autonomous mode is provided. The vehicle is configured to obtain an indication of a final destination, and, if the final destination is not on a pre-approved road for travel by the vehicle, the vehicle is configured to determine a route from the vehicle's current location to an intermediary destination. The vehicle is further configured to determine a means for the vehicle user to reach the final destination from the intermediate destination.

Aspects of embodiments to systems and methods for navigating a mobile platform using an imaging device on the platform, from a point of origin towards a target located in a scene, and without requiring a Global Navigation Satellite system (GNSS), by employing the following steps: acquiring, by the imaging device, an image of the scene comprising the target; determining, based on analysis of the image, a direction vector pointing from the mobile platform to the target; advancing the mobile platform in accordance with the direction vector to a new position; and generating, by a distance sensing device, an output as a result of attempting to determine, with the distance sensing device, a distance between the mobile platform and the target. The mobile platform advanced towards the target until the output produced by the distance sensing device is descriptive of a distance which meets a low-distance criterion.

Aspects of embodiments to systems and methods for navigating a mobile platform using an imaging device on the platform, from a point of origin towards a target located in a scene, and without requiring a Global Navigation Satellite system (GNSS), by employing the following steps: acquiring, by the imaging device, an image of the scene comprising the target; determining, based on analysis of the image, a direction vector pointing from the mobile platform to the target; advancing the mobile platform in accordance with the direction vector to a new position; and generating, by a distance sensing device, an output as a result of attempting to determine, with the distance sensing device, a distance between the mobile platform and the target. The mobile platform advanced towards the target until the output produced by the distance sensing device is descriptive of a distance which meets a low-distance criterion.

A system searches for a track for a vehicle to travel automatically. The system includes a processor. The processor includes a route search unit, a restriction condition generation unit, and a track search unit. The route search unit searches for a series having elements of a position and posture of the vehicle, which is a route for moving from an initial position to a target position of the vehicle, based on a first restriction condition representing a position of an obstacle. The restriction condition generation unit generates a second restriction condition in which a penalty value increases according to a deviation distance from the route. The track search unit searches for a series having elements of a position, posture, speed, and steering angle of the vehicle, which is a track for moving from the initial position to the target position of the vehicle, based on the second restriction condition.

Systems and methods of the present invention are provided to generate a plurality of flight trajectories that do not conflict with other aircraft in a local area. Interventions by an air traffic control system help prevent collisions between aircraft, but these interventions can also cause an aircraft to substantially deviate from the pilot's intended flight trajectory, which burns fuels, wastes time, etc. Systems and methods of the present invention can assign a standard avoidance interval to other aircraft in the area such that a pilot's aircraft does not receive an intervention by an air traffic control system. Systems and methods of the present invention also generate a plurality of conflict-free flight trajectories such that a pilot or an automated system may select the most desirable flight trajectory for fuel efficiency, speed, and other operational considerations, etc.

A motion planner of an autonomous vehicle's computer system uses reconfigurable collision detection architecture hardware to perform a collision assessment on a planning graph for the vehicle prior to execution of a motion plan. For edges on the planning graph, which represent transitions in states of the vehicle, the system sets a probability of collision with a dynamic object in the environment based at least in part on the collision assessment. Depending on whether the goal of the vehicle is to avoid or collide with a particular dynamic object in the environment, the system then performs an optimization to identify a path in the resulting planning graph with either a relatively high or relatively low potential of a collision with the particular dynamic object. The system then causes the actuator system of the vehicle to implement a motion plan with the applicable identified path based at least in part on the optimization.

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.

The present disclosure provides systems and methods that control the motion of an autonomous vehicle by rewarding or otherwise encouraging progress toward a goal, rather than simply rewarding distance travelled. In particular, the systems and methods of the present disclosure can project a candidate motion plan that describes a proposed motion path for the autonomous vehicle onto a nominal pathway to determine a projected distance associated with the candidate motion plan. The systems and methods of the present disclosure can use the projected distance to evaluate a reward function that provides a reward that is positively correlated to the magnitude of the projected distance. The motion of the vehicle can be controlled based on the reward value provided by the reward function. For example, the candidate motion plan can be selected for implementation or revised based at least in part on the determined reward value.

A laser robot path planning method includes: obtaining a target start point and a target end point of a laser robot; determining, based on a first map, whether the target start point and the target end point of the laser robot are located within a same area; in a case that the target start point and the target end point are located within the same area, planning a movement path based on the first map using the target start point and the target end point; and in a case that the target start point and the target end point are located within different areas, expanding a passable area of the first map based on several passable line segments in a second map, and planning the movement path based on the expanded first map, the target start point, and the target end point.

A vehicle includes a motor and a controller configured to provide a traveling application of an own vehicle including the motor and to provide a non-traveling application of the own vehicle. The controller is further configured to: determine whether the own vehicle is providing the traveling application or the non-traveling application; generate usage information of an application being provided, based on a result of the determination of whether the own vehicle is providing the traveling application or the non-traveling application; and inform an outside of the usage information.