A towable element for a lawnmower, the towable element includes a carriage defining a work tool receiving area; an engagement feature coupled to the carriage, wherein the engagement feature removably interfaces with a complementary engagement feature of the lawnmower to selectively couple the towable element with the lawnmower; and a work tool removably disposed at the work tool receiving area, wherein the work tool acts on an underlying ground surface below the towable element.

A movable lighting apparatus for raising natural lawn grass includes a frame, main support legs supporting the frame, and casters attached to the lower ends of the main support legs. A movable beam is provided such that it can be advanced and retracted relative to the frame in a left-right direction. A stationary beam is fixed to the frame. A sub-support leg is provided at an advancement direction forward end portion of the movable beam so as to support a distal end of the movable beam when the movable beam is advanced. A caster is attached to the lower end of the sub-support leg. LED lamps are attached to the movable beam and the stationary beam. When the movable beam is retracted, the lower end of the caster of the sub-support leg is moved to a position above the lower ends of the casters of the main support legs.

A lawn care apparatus which can be mounted on a mobile unit and includes a digital camera, which can be oriented towards the lawn, and a control device and at least one tool which can be controlled by the control device and can be lowered to the lawn by a motor. The images from the digital camera are supplied to an algorithm implemented in the control device to perform object recognition so that upon recognition of an object, the control device lowers the tool in order for a work step to be performed on the object.

A lawn care apparatus which can be mounted on a mobile unit and includes a digital camera, which can be oriented towards the lawn, and a control device and at least one tool which can be controlled by the control device and can be lowered to the lawn by a motor. The images from the digital camera are supplied to an algorithm implemented in the control device to perform object recognition so that upon recognition of an object, the control device lowers the tool in order for a work step to be performed on the object.

A ground surface treatment vehicle and systems and methods using the same. In some embodiments, the vehicle may be adapted to autonomously or semi-autonomously identify and optionally treat target areas such as divots on turf surfaces. The vehicle may identify the target area via onboard or remote sensors and autonomously treat the target area by providing a treating material such as infill, seed, particulate matter, and liquids.

A ground surface treatment vehicle and systems and methods using the same. In some embodiments, the vehicle may be adapted to autonomously or semi-autonomously identify and optionally treat target areas such as divots on turf surfaces. The vehicle may identify the target area via onboard or remote sensors and autonomously treat the target area by providing a treating material such as infill, seed, particulate matter, and liquids.

Embodiments of a golf course maintenance drone include a housing and a wing assembly coupled to the housing, the wing assembly including a propeller that is configured to provide lift to the housing. In addition, the drone includes a golf course maintenance assembly coupled to the housing. The golf course maintenance assembly is configured to fill divots, repair pitch marks, rake bunkers, or collect debris on the golf course.

Embodiments of a golf course maintenance drone include a housing and a wing assembly coupled to the housing, the wing assembly including a propeller that is configured to provide lift to the housing. In addition, the drone includes a golf course maintenance assembly coupled to the housing. The golf course maintenance assembly is configured to fill divots, repair pitch marks, rake bunkers, or collect debris on the golf course.

Systems and methods are provided to assess light conditions at a location. The system can include a computer processor (CP) and a database. The database can store a grid map that includes a plurality of grid areas that segregate the location. The system can include a location sensor and a light sensor that generates sensor light. The CP can perform processing including: (1) determining that a sample event has been attained; (2) inputting sample data including location data and light data, (3) identifying, based on the location data, a grid area, of the plurality of grid areas, that corresponds to the location data; and (4) associating, based on the identifying, the sample with the grid area. The processing can further include (5) aggregating the sample with a previous sample that has been associated with the grid area; (6) generating a light value result based on the light level value and the previous light level value; and (7) applying the light value.

A method operates a hand-guided processing device having a user-activated operating sensor device with a plurality of different detection positions. The method involves the steps: a) detecting a sequence of activations of the operating sensor device at different detection positions of the plurality of detection positions, and b) when the detected sequence corresponds to a given sequence, calibrating the operating sensor device for at least one detection position of the plurality of detection positions based on at least one of the activations of the detected activations.