Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Vehicle collision and/or smart home incident monitoring, damage detection, and responses are also described, with particular focus on the particular challenges associated with incident response for unoccupied vehicles and/or smart homes. Operating data associated with the autonomous vehicle and/or smart home may be received. Within the operating, an unusual condition indicative of a likelihood of incident may be detected. Based on the unusual condition, it may be determined that the incident occurred. Accordingly, a response to the incident may be determined. The response may be implemented by the autonomous vehicle and/or smart home.

Disclosed is a system for controlling navigation of a robot in a dynamic environment based on heuristic learning. The system comprising: a heuristic learning unit configured to determine at least a preferred path, a preferred position, and a preferred orientation for the robot based on human robot interaction (HRI) during navigation of the robot and a path scaling factor and a navigation control unit configured to generate at least one of: an optimal path, an optimal position, and an optimal orientation, for navigation of the robot in the dynamic environment in real-time, during navigation of the robot, based on at least one of: the preferred path, the preferred position, the preferred orientation or a previous navigation data associated with the robot.

Disclosed is a system for controlling navigation of a robot in a dynamic environment based on heuristic learning. The system comprising: a heuristic learning unit configured to determine at least a preferred path, a preferred position, and a preferred orientation for the robot based on human robot interaction (HRI) during navigation of the robot and a path scaling factor and a navigation control unit configured to generate at least one of: an optimal path, an optimal position, and an optimal orientation, for navigation of the robot in the dynamic environment in real-time, during navigation of the robot, based on at least one of: the preferred path, the preferred position, the preferred orientation or a previous navigation data associated with the robot.

A movement control system (1000) includes at least one moving body (1), a sensor (3) configured to transmit movement region information related to a movement region of the moving body, a route generating unit (440) configured to generate a route for the moving body to move through the movement region, based on the movement region information received via a network, and a moving body control unit (450) configured to control movement of the moving body, based on the route. The route generating unit is configured to generate an avoidance route for avoiding a second region including a first region representing a position of an object existing in the movement region and a surrounding region at the first region. The moving body control unit is configured to control the moving body based on the avoidance route.

A movement control system (1000) includes at least one moving body (1), a sensor (3) configured to transmit movement region information related to a movement region of the moving body, a route generating unit (440) configured to generate a route for the moving body to move through the movement region, based on the movement region information received via a network, and a moving body control unit (450) configured to control movement of the moving body, based on the route. The route generating unit is configured to generate an avoidance route for avoiding a second region including a first region representing a position of an object existing in the movement region and a surrounding region at the first region. The moving body control unit is configured to control the moving body based on the avoidance route.

Methods and systems for identifying autonomous vehicle users are described herein. An autonomous vehicle may receive a request to pick up a user at a starting location and transport the user to a destination location. Accordingly, the autonomous vehicle may travel to the starting location. Upon arriving at the starting location, the autonomous vehicle may detect whether a person approaching the vehicle is the user by detecting a biometric identifier for the person. The biometric identifier may then be compared to a biometric fingerprint for the user, and if there is a match, the autonomous vehicle may determine that the person is the user. As a result, the user may be allowed to enter the autonomous vehicle and/or the autonomous vehicle may begin travelling to the destination location. Otherwise, the person may be denied entry to the autonomous vehicle.

The present invention relates to a method and apparatus to determine the position of an image sensor relative to a predetermined continuous pattern of colors and/or objects based on the images said patterns of colors and/or objects produces within the image sensor.

The present invention relates to a method and apparatus to determine the position of an image sensor relative to a predetermined continuous pattern of colors and/or objects based on the images said patterns of colors and/or objects produces within the image sensor.

Systems and methods are provided for collecting anonymized drive information. A processing device may be configured to receive outputs from one or more sensors; determine at least one motion representation for the host vehicle based on the outputs; receive at least one image representative of an environment of the host vehicle; analyze the at least one image to determine at least one road characteristic associated with a road section; assemble first road segment information relative to a first portion of the road section, wherein the first portion of the road section is separated from a starting point associated with a route traveled by the host vehicle; assemble second road segment information relative to a second portion of the road section; and cause transmission of the first road segment information and the second road segment information to a server for assembly of an autonomous vehicle road navigation model.

A control device (200) includes a ground vehicle controller (230) that causes a ground vehicle to travel at a target area, an acquirer (210) that acquires state information expressing a state of a surface of the target area while the ground vehicle travels the target area, and a determiner (240) that determines, based on the acquired state information, whether or not an aircraft is landable at the target area.