A robotic lawnmower arranged to operate in an outdoor operational area, the robotic lawnmower comprising a visual sensor, and wherein the robotic lawnmower is configured for detecting an object and determine that the object is a woody plant based on an image received from the visual sensor, determining an outer extension of the woody plant, and then traversing the outer extension of the woody plant traversal towards an inner extension to enable cutting grass also in the area between the outer and inner extensions.

An aircraft system having a LIDAR system, one or more sensors, and a control unit. The control unit includes processing circuitry configured to calculate during flight a pressure altitude, calibrated airspeed, Mach number, equivalent airspeed, static temperature, static pressure, and dynamic pressure of an aircraft based on a combination of air data measurements from the LIDAR system and the one or more sensors.

Providing avatar support for trapped seismic event survivors is provided. A survivor is detected in debris of a collapsed structure using a set of sensors. An avatar communicates with the survivor. Fresh air flow drawn from different directions is measured to detect a pathway through the debris to an environment outside the collapsed structure. The pathway is detected through the debris to the environment outside the collapsed structure based on measuring the fresh air flow drawn from the different directions.

A drone training method includes: inputting a plurality of wind speed components into a corresponding plurality of fuzzy functions, to generate a plurality of wind speed membership values respectively; selecting one from the plurality of wind speed membership values corresponding to each of the wind speed components, and generating a rule value based on the wind speed membership values corresponding to each of the wind speed components; inputting the plurality of wind speed components into one of inference functions, where each rule value corresponds to one of the inference functions as a weight respectively, and calculating a function sum of a plurality of inference functions corresponding to each of the wind speed components; generating a regression model after calculating an error function base on each offset component and the function sum corresponding to each of the wind speed components and optimizing the error function.