A method for monitoring an unmanned aerial vehicle (UAV) includes a processor obtaining a datagram based on monitoring data for a UAV-detector communication between the UAV and one or more detectors. The monitoring data indicates at least one of a location of the UAV or a location of a control station in communication with the UAV. The method further includes determining a risk level by retrieving pre-stored risk information associated with the UAV based on the datagram.

A cleaning area estimation device (30) includes an estimation unit (33) that estimates dirt information (D2) about an inside of a cleaning area on the basis of image information (D1) obtained by imaging a cleaning area by an imaging device (10), and a generation unit (34) that generates map information (D3) indicating a map of the dirt information about the cleaning area on the basis of the estimated time-series dirt information (D2).

An information presentation method that is executed by a computer includes acquiring travelling path information that includes a cleaning path and a relocation path, the cleaning path showing positions cleaned by a self-propelled vacuum cleaner in each of a plurality of regions included in a specific area, and the relocation path showing a route of the self-propelled vacuum cleaner that has travelled from one region to another region different from the one region out of the regions, the route being included in the specific area; generating presentation information that includes the cleaning path and the relocation path and that changes the mode of display of at least one of the cleaning path or the relocation path when a specific condition is satisfied; and presenting the presentation information to the user as the travelling path of the self-propelled vacuum cleaner in the specific area.

An agriculture support device includes a traveling creator to create a scheduled traveling route of an agricultural machine in an agricultural field, a display controller to display on an external terminal a virtual traveling status of the agricultural machine to travel on the scheduled traveling route created by the traveling creator, and a correction permitting controller to permit correction of the scheduled traveling route created by the traveling creator when the external terminal requests the correction. The display controller displays, on the external terminal, the virtual traveling status and a result traveling status of the agricultural machine that has traveled on the scheduled traveling route.

A processor coupled to memory is configured to receive an identification of a geographical location associated with a target specified by a user remote from a vehicle. A machine learning model is utilized to generate a representation of at least a portion of an environment surrounding the vehicle using sensor data from one or more sensors of the vehicle. At least a portion of a path to a target location corresponding to the received geographical location is calculated using the generated representation of the at least portion of the environment surrounding the vehicle. At least one command is provided to automatically navigate the vehicle based on the determined path and updated sensor data from at least a portion of the one or more sensors of the vehicle.

A method for controlling an autonomous, mobile robot which is designed to navigate independently in a robot deployment area, using sensors and a map. According to one embodiment, the method comprises detecting obstacles and calculating the position of detected obstacles based on measurement data received by the sensors, and controlling the robot to avoid a collision with a detected obstacle, the map comprising map data that represents at least one virtual blocked region which, during the control of the robot, is taken into account in the same way as an actual, detected obstacle.

A method and system provide the ability to manage an orchard. Sensor data that represents a first state of the orchard is captured via one or more sensors. The sensor data is captured as the one or more sensors are traveling through the orchard. An almanac is maintained. The almanac provides a state library of sequential states of a representative orchard and a task library for one or more tasks to be performed to transition between the sequential states. A task manager queries the almanac to identify a first task of the one or more tasks and allocates the first task to one or more robots that perform the first task.

A map management system stores map information used by an automated driving vehicle. The automated driving vehicle detects an obstacle based on the map information, or acquires a margin distance when stopping in front of an obstacle based on the map information. When requiring a remote operator's decision about an action with respect to the obstacle, the automated driving vehicle issues a support request that requests the remote operator to give support. The map management system acquires an operator instruction to the automated driving vehicle issued by the remote operator in response to the support request. The map management system estimates a type of the obstacle based on a state of acquisition of the operator instruction or a content of the operator instruction. Then, the map management system updates the map information according to the type of the obstacle.

A method of operating an autonomous cleaning robot is described. The method includes initiating a training run of the autonomous cleaning robot and receiving, at a mobile device, location data from the autonomous cleaning robot as the autonomous cleaning robot navigates an area. The method also includes presenting, on a display of the mobile device, a training map depicting portions of the area traversed by the autonomous cleaning robot during the training run and presenting, on the display of the mobile device, an interface configured to allow the training map to be stored or deleted. The method also includes initiating additional training runs to produce additional training maps and presenting a master map generated based on a plurality of stored training maps.

A bio-hybrid odor-localizing autonomous air vehicle includes an airborne robotic platform having a navigation platform, a wireless transmitter communicatively coupled to a management console, and a biological sensor mounted on the airborne robotic platform that reacts to at least one olfactory odor. A controller is communicatively coupled to the airborne robotic platform, the navigation platform, and the biological sensor. The controller monitors the biological sensor. In response to the biological sensor detecting the at least one olfactory odor, the controller directs the airborne platform to three-dimensionally map an olfactory plume of the at least one olfactory odor using an olfactory-driven search pattern. The controller stores the three-dimensional map for later retrieval or transmits the three-dimensional map of the olfactory plume to the management console via the wireless transmitter.