Described herein are methods and systems for generating shared collaborative maps for planting or harvesting operations. A method of generating a collaborative shared map between machines includes generating a first map for a first machine based on a first set of data and generating a second map for a second machine based on a second set of data. The method further includes generating at least one shared collaborative map for at least one of the first and second machines based on the first and second maps.

Described herein are methods and systems for generating shared collaborative maps for planting or harvesting operations. A method of generating a collaborative shared map between machines includes generating a first map for a first machine based on a first set of data and generating a second map for a second machine based on a second set of data. The method further includes generating at least one shared collaborative map for at least one of the first and second machines based on the first and second maps.

Systems, devices, and methods for scheduling and controlling a mobile cleaning robot based on a seasonal or environmental debris accumulation event are discussed. A mobile cleaning robot receives a seasonal cleaning schedule corresponding to a seasonal or environmental debris accumulation event. The seasonal cleaning schedule includes instructions to clean a portion of the mobile robot's environment having a debris state varied seasonally. The mobile cleaning robot executes a cleaning mission in the environment in accordance with the seasonal cleaning schedule.

Systems, devices, and methods for scheduling and controlling a mobile cleaning robot based on a seasonal or environmental debris accumulation event are discussed. A mobile cleaning robot receives a seasonal cleaning schedule corresponding to a seasonal or environmental debris accumulation event. The seasonal cleaning schedule includes instructions to clean a portion of the mobile robot's environment having a debris state varied seasonally. The mobile cleaning robot executes a cleaning mission in the environment in accordance with the seasonal cleaning schedule.

A setting processing unit sets a predetermined turning route among a plurality of turning routes having different turning methods, for each of a plurality of work paths included in a field where a work vehicle autonomously travels in accordance with a target route and sets the target route including the turning route set for each of the plurality of work paths and a work route set corresponding to the field.

A cleaning robot includes a detector configured to detect an obstacle; a determining circuit configured to determine whether the cleaning robot is in an obstacle obstruction state; and a controller configured to control the first drive wheel to cross an obstacle and control the second drive wheel to cross the obstacle according to a detection result when the cleaning robot is in the obstacle obstruction state, wherein the detector is further configured to detect whether the first drive wheel crosses the obstacle; and the controller is further configured to control the second drive wheel to cross the obstacle when the detector detects that the first drive wheel crosses the obstacle.

The present disclosure provides various advancements for mobile and automated processing utilizing additive manufacturing. The present disclosure includes methods for the utilization of mobile and automated processing apparatus and may include examples of sealcoating operations. In some examples, omnidirectional drive systems such as Mecanum wheels may create novel operational aspects. Artificial intelligence techniques may enhance operations and may be used to create model for the processing apparatus.

A cleaning route determination system includes an analyzer that analyzes behavior of airflow and particles inside a facility, a map generator that generates a dust accumulation map indicating one or more dust accumulation areas inside the facility and one or more dust amounts corresponding to the one or more dust accumulation areas, and a route calculator that determines a first route from second routes. Each of the second routes is a route for a cleaner to pass through, within a certain period of time, at least one of the one or more dust accumulation areas. A total amount indicating a sum of dust amounts corresponding to dust accumulation areas included the first route is largest among total amounts corresponding to the second routes, each of the total amounts indicating a sum of dust amounts corresponding to dust accumulation areas included in each of the second routes.

Spatiotemporal robotic navigation may include providing a set of robots non-conflicting access to the same shared resources at different times so that the robots may operate without continually accounting for the locations of the other robots and workers operating in the particular site, without continually planning or updating paths after determining an initial path, and without continuously adjusting movements as the robots near one another. The spatiotemporal robotic navigation involves generating spatiotemporal plans. Each plan has a set of objectives that a robot is to execute by different time intervals. Each plan is generated so as to not conflict with the resources being accessed by other robots at time intervals set in the plans of other robots.

Spatiotemporal robotic navigation may include providing a set of robots non-conflicting access to the same shared resources at different times so that the robots may operate without continually accounting for the locations of the other robots and workers operating in the particular site, without continually planning or updating paths after determining an initial path, and without continuously adjusting movements as the robots near one another. The spatiotemporal robotic navigation involves generating spatiotemporal plans. Each plan has a set of objectives that a robot is to execute by different time intervals. Each plan is generated so as to not conflict with the resources being accessed by other robots at time intervals set in the plans of other robots.