Abstract: A vegetative health mapping system which creates two- or three-dimensional maps and associates moisture content, soil density, ambient light, surface temperature, and/or additional indications of vegetative health with the map. Moisture content is inferred using radar return signals of near-field and/or far-field radar. By tuning various parameters of the one or more radar (e.g. frequency, focus, power), additional data may be associated with the map from subterranean features (such as rocks, soil density, sprinklers, etc.). Additional sensors (camera(s), lidar, IMU, GPS, etc.) may be fused with radar returns to generate maps having associated moisture content, surface temperature, ambient light levels, additional indications of vegetative health (as may be determined by machine learned algorithms), etc. Such vegetative health maps may be provided to a user who, in turn, may indicate additional areas for the vegetative health device to scan or otherwise used to recommend and/or perform treatments.

Abstract: Systems and techniques for detecting a difference in orientation between a lawn mower and a surface on which the mower is mowing, or between portions of such surface, based on one or more of sensor data or map data are discussed. The difference in orientation may then be used to control the lawn mower by, for example, raising a deck height or idling a blade speed, though other actuations are contemplated. In some examples, an amount the deck height is raised may be based on the difference in orientation. Based on a subsequent difference detected being at or below a threshold difference, the mower may return to previous operating conditions including, but not limited to, returning a blade speed to a previous blade speed and/or returning the deck height to a previous deck height, among other controls.

Abstract: Systems and techniques for generating a set of connected segments for a device or system to traverse in order to reach every point of the region (a coverage plan). Nodes defining the region to be traversed define a polygon. The polygon is decomposed into a mesh and a graph of the mesh is generated. The graph may be used to determine a longest funneled path which, in turn, may be used to either optimize for a longest path or to divide the polygon for eroding sides. The longest path and/or erosions are used to define a set of segments. The segments are connected, which in some examples is done via an optimization to minimize an amount of time or energy to traverse all segments and connections. The resultant coverage plan is sent to a system configured to receive the plan and traverse the region.

Abstract: Systems and techniques for detecting suboptimal mowing due to impacted vegetation and/or orientation changes are discussed. In some examples, blade speeds, blade heights, torques, and/or a current required to spin the blades of a mower at a determined rate may be calibrated and associated with a lawn mower and/or map. Changes in any one or more of the blade speed, current required, torque, etc. (and/or additional data from one or more sensors on the mower) may be used as an indication for determining whether vegetation has impacted the underside of a mower, whether the blade has struck an object, whether the mower is undergoing an orientation change, whether the mower requires maintenance, and the like. Based on the indication, the mower can perform one or more functions to attempt to remediate the problem autonomously and/or send a signal to a user for additional help.

Abstract: A vegetative health mapping system which creates two- or three-dimensional maps and associates moisture content, soil density, ambient light, surface temperature, and/or additional indications of vegetative health with the map. Moisture content is inferred using radar return signals of near-field and/or far-field radar. By tuning various parameters of the one or more radar (e.g. frequency, focus, power), additional data may be associated with the map from subterranean features (such as rocks, soil density, sprinklers, etc.). Additional sensors (camera(s), lidar, IMU, GPS, etc.) may be fused with radar returns to generate maps having associated moisture content, surface temperature, ambient light levels, additional indications of vegetative health (as may be determined by machine learned algorithms), etc. Such vegetative health maps may be provided to a user who, in turn, may indicate additional areas for the vegetative health device to scan or otherwise used to recommend and/or perform treatments.