Among other things, techniques are described for predicting how an agent (e.g., a vehicle, bicycle, pedestrian, etc.) will move in an environment based on prior movement, the road network, the surrounding objects and/or other relevant environmental factors. One trajectory prediction technique involves generating a probability map for an agent's movement. Another trajectory prediction technique involves generating a trajectory lattice, for an agent's movement. In addition, a different trajectory prediction technique involves multi-modal regression where a classifier (e.g., a neural network) is trained to classify the probability of a number of (learned) modes such that each model produces a trajectory based on the current input.

Among other things, techniques are described for predicting how an agent (e.g., a vehicle, bicycle, pedestrian, etc.) will move in an environment based on prior movement, the road network, the surrounding objects and/or other relevant environmental factors. One trajectory prediction technique involves generating a probability map for an agent's movement. Another trajectory prediction technique involves generating a trajectory lattice, for an agent's movement. In addition, a different trajectory prediction technique involves multi-modal regression where a classifier (e.g., a neural network) is trained to classify the probability of a number of (learned) modes such that each model produces a trajectory based on the current input.

Various implementations disclosed herein include devices, systems, and methods that enable improved display of virtual content in computer generated reality (CGR) environments. In some implementations, the virtual content includes a reminder associated with a user and the user's physical environment.

Various implementations disclosed herein include devices, systems, and methods that enable improved display of virtual content in computer generated reality (CGR) environments. In some implementations, the virtual content includes a reminder associated with a user and the user's physical environment.

An aerological sonde for measuring meteorological conditions in a cyclonic storm, the aerological sonde including a sonde casing having an outer casing surface and measurement unit arranged inside the sonde casing. The outer casing surface is arranged to form a sole drag surface of the aerological sonde such that a self-sustaining aerological sonde is formed. The measurement unit of the self-sustaining aerological sonde includes a turbulence sensor arranged to measure change of movement of the self-sustaining aerological sonde.

An aerological sonde for measuring meteorological conditions in a cyclonic storm, the aerological sonde including a sonde casing having an outer casing surface and measurement unit arranged inside the sonde casing. The outer casing surface is arranged to form a sole drag surface of the aerological sonde such that a self-sustaining aerological sonde is formed. The measurement unit of the self-sustaining aerological sonde includes a turbulence sensor arranged to measure change of movement of the self-sustaining aerological sonde.

An improved silent, adjustable, hands free optical viewing device that allows a hunter to obtain real time ranges to a target or an enhanced view of a target with a minimum of noise and motion. A variation allows the mounting of a video camera to capture video of the hunt.

An improved silent, adjustable, hands free optical viewing device that allows a hunter to obtain real time ranges to a target or an enhanced view of a target with a minimum of noise and motion. A variation allows the mounting of a video camera to capture video of the hunt.

A measurement vehicle (101) acquires measurement environment data indicating a measurement environment from a measurement system and transmits the acquired measurement environment data to a base station (104). The measurement vehicle (101) receives movement measurement instruction data indicating an instruction on the movement measurement from the base station (104). The measurement vehicle (101) controls the measurement system in accordance with the instruction indicated by the received movement measurement instruction data.

A measurement vehicle (101) acquires measurement environment data indicating a measurement environment from a measurement system and transmits the acquired measurement environment data to a base station (104). The measurement vehicle (101) receives movement measurement instruction data indicating an instruction on the movement measurement from the base station (104). The measurement vehicle (101) controls the measurement system in accordance with the instruction indicated by the received movement measurement instruction data.