Some aspects provide a method for instructing operation of a robotic floor-cleaning device based on the position of the robotic floor-cleaning device within a two-dimensional map of the workspace. A two-dimensional map of a workspace is generated using inputs from sensors positioned on a robotic floor-cleaning device to represent the multi-dimensional workspace of the robotic floor-cleaning device. The two-dimensional map is provided to a user on a user interface. A user may adjust the boundaries of the two-dimensional map through the user interface and select settings for map areas to control device operation in various areas of the workspace.

A method for aircraft flight path generation includes, at a computing system, receiving, for a plurality of waypoints in a geographic area, predicted aircraft noise levels for an aircraft at each waypoint of the plurality of waypoints, the predicted aircraft noise levels predicted based at least in part on a plurality of flight parameters for the aircraft. The predicted aircraft noise levels are input to a flight path prediction system configured to generate a candidate flight path for the aircraft through the geographic area based at least in part on the predicted aircraft noise levels. The candidate flight path is output from the flight path prediction system, wherein the candidate flight path is predicted to result in less ground-level noise when followed by the aircraft as compared to an alternate flight path through the geographic area.

A technique for managing an airspace used by a fleet of UAVs includes presenting a user interface (UI) adapted for creating an airspace restriction based on non-digitized information available to a human supervisor and input into the UI by the human supervisor, soliciting with a selectable field of the UI a restriction type for the airspace restriction from a plurality of available restriction types, soliciting with duration fields of the UI start and end times for the airspace restriction, soliciting with location fields of the UI a location of the airspace restriction, creating a new entry for the airspace restriction in a restriction data store based on the selectable, duration, and location fields, and creating a new flight mission or altering an existing flight mission based upon the airspace restriction.

A computer-implemented system and method relate a mobile robot. State data is generated using sensor data from at least one sensor. A current confident zone is identified on a unified confident zone map using the state data. The unified confident zone map includes confident zones. Each confident zone is indicative of a given confidence level of given state data of a selected sensor modality for a given location. Assessment data is generated that indicates whether the current confident zone is deemed a failure zone. A mobile robot is controlled based on a control command. The control command relates to a recovery plan of moving the mobile robot out of the current confident zone when the assessment data indicates that the current confident zone is the failure zone. The control command relates to another plan when the assessment data indicates that the current confident zone is not the failure zone.

Some aspects provide a method for instructing operation of a robotic floor-cleaning device based on the position of the robotic floor-cleaning device within a two-dimensional map of the workspace. A two-dimensional map of a workspace is generated using inputs from sensors positioned on a robotic floor-cleaning device to represent the multi-dimensional workspace of the robotic floor-cleaning device. The two-dimensional map is provided to a user on a user interface. A user may adjust the boundaries of the two-dimensional map through the user interface and select settings for map areas to control device operation in various areas of the workspace.

A method for guiding an autonomous aircraft, the aircraft includes an automatic pilot, a plurality of sensors and an imaging unit, the aircraft being configured to fly over a geographic zone comprising overflight prohibited zones, the guidance method can advantageously comprise a phase of real flight of the autonomous aircraft by using a given guidance law, comprising the following steps: determining a current state of the autonomous aircraft; determining an optimum action to be executed by using a neural network receiving the current state; determining a plurality of control instructions compatible with the guidance law based on the optimum action to be executed; transmitting to the automatic pilot the plurality of control instructions, which provides a new state of the autonomous aircraft.

A travel control method for the work vehicle is to cause the work vehicle to autonomously travel along a work route. The travel control method includes causing the work vehicle to perform a non-turning back-and-forth travel. In the non-turning back-and-forth travel, after the work vehicle 1 travels from a first end toward a second end of the work rote, the work vehicle reverses a traveling direction without changing an orientation thereof on a second end side and travels from the second end toward the first end.

Techniques are directed to controlling a mower. Such techniques involve initiating an automated mowing task that directs the mower to operate in a geographic area defined by a virtual boundary. Such techniques further involve electronically detecting presence of a device within the geographic area defined by the virtual boundary. Such techniques further involve suspending the automated mowing task in response to detecting the presence of the device within the geographic area defined by the virtual boundary.

A precision landing system is described for an unmanned aerial vehicle (UAV). The system may include one or more anchors configured for placement in proximity to a landing zone, a tag configured for securement to the UAV where the tag wirelessly communicates with at least three or more of the anchors. A controller may be configured to fly the UAV towards a centerline axis defined through a first airspace zone at a first altitude above the landing zone while descending towards the first altitude and then fly the UAV towards the centerline axis defined through a second airspace zone at a second altitude which is below the first altitude while descending towards the second altitude, and finally to fly the UAV towards the centerline axis defined through a third airspace zone at a third altitude which is below the second altitude while descending towards the landing zone.

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.