The present application discloses a sweeping method of a swimming pool cleaning robot and a cleaning robot, the method including: acquiring map information about an area to be cleaned; planning a first sweeping path based on the map information, the first sweeping path meeting pre-set cleaning parameter requirements; controlling the cleaning robot to travel and perform a cleaning operation based on the first sweeping path; determining whether the cleaning operation is ended, and if so, controlling the cleaning robot to travel to a missed area so as to perform supplementary sweeping. This application can improve sweeping coverage rate and sweeping efficiency.

A vegetation monitoring device with at least one camera unit (28) for monitoring vegetation health in a garden (10), wherein the at least one camera unit (28) is configured to detect the garden area (30, 32, 34) in at least a first range of the electromagnetic spectrum, in particular in the visible light range, and in at least a second region of the electromagnetic spectrum, in particular in the infrared range, in order to determine at least one vegetation index of at least one garden area (30, 32, 34) of the garden (10), in particular in the region of visible light, and in at least one second region of the electromagnetic spectrum, in particular in the infrared range, wherein the camera unit (28) is provided for an arrangement at least substantially above ground level of the garden (10) and for an at least substantially stationary arrangement outside or in the vicinity of the garden (10), and a vegetation monitoring system is proposed.

Techniques and systems are provided for image generation. For instance, a process can include obtaining remote sensing information from a user device, wherein the remote sensing information comprises at least one of 6-degrees-of-freedom (6DOF) trajectory information or presence information; obtaining an environment map from the robot device; reorienting the remote sensing information based on a determined offset and rotation for the remote sensing information; applying the offset and rotation to the remote sensing information to identify portions of the environment map that include detected objects; determining candidate areas for movement of the robot device based on the portions of the environment map that include the detected objects; and outputting the candidate areas for movement of the robot device for transmission to the robot device.

A method for operating a self-propelled robotic lawnmower that is configured to operate in a pseudo random pattern in a work area may include driving means, processing means, and a camera. The method includes detecting a rough grass patch condition, defined as an estimated ratio of uncut to cut grass in the work area falling below a threshold. Then, a rough grass patch is identified using the camera, and the lawnmower steers towards and processes the identified rough patch.

A method for controlling a mobile, self-propelled appliance, in particular a floor cleaning appliance such as a robot vacuum cleaner and/or a sweeper and mopping robot so as to mop up an accumulation of liquid, includes driving on a floor surface intended for cleaning in a direction of travel in a forward movement of the appliance and cleaning the floor surface by using a dry cleaning module and/or a wet cleaning module of the appliance. The accumulation of liquid is detected in the direction of travel in front of the appliance in a moist area. The forward movement in front of the moist area is terminated and the appliance is rotated about substantially 180. Driving on the moist area in a reversing movement in the direction of travel of the appliance and mopping up the accumulation of liquid using the wet cleaning module is carried out.

Systems and methods for configuring, planning, and executing autonomous mowing operations in a turf environment using an autonomous mowing machine are described. The system determines external and internal boundaries of a property through position data (e.g., GPS, odometry) and visual information from onboard sensors. The collected information is used to create digital fences and zone boundaries. Objects within the mowing area are classified as transient or non-transient, with corresponding autonomous actions assigned. Boundaries and object data inform path planning, dynamically updating routes in response to environmental changes, object reclassification, or operator input via a client device. The machine executes the planned actions in real time, adjusting various operational parameters as it traverses the turf environment.