Embodiments of the present disclosure provide a method and apparatus for determining a velocity of an obstacle, a device, and a medium. An implementation includes: acquiring a first point cloud data of the obstacle at a first time and a second point cloud data of the obstacle at a second time; registering the first point cloud data and the second point cloud data by moving the first point cloud data or the second point cloud data; and determining a moving velocity of the obstacle based on a distance between two data points in a registered data point pair.

Systems and methods for determining a velocity of a fluid or an object are described. Systems and methods include receiving image data of the fluid or the object, the image data comprising a plurality of frames. Each frame comprises an array of pixel values. Systems and methods include creating a frame difference by subtracting an array of pixel values for a first frame of the image data from an array of pixel values for a second frame of the image data. Systems and methods include measuring a difference between a location of the object in the first frame of the image data and the second frame of the image data. Systems and methods include creating a correlation matrix based on the measured difference. Systems and methods include using the frame difference and the correlation matrix to automatically determine the velocity of the fluid or the object.

Techniques are provided for determining a moving body's position and velocity in the presence of motion of a measuring device relative to the body. For example, a swimmer's position and velocity may be determined by compensating for bias that may result from a swimmer's arm swing. This may help avoid over-estimating a swimmer's velocity that results in inaccurate position estimation along the swimmer's path. To compensate for the swimmer's arm swing, an estimate of translational velocity due to arm rotation may be removed, e.g., from pseudo-range rates (PRRs) from satellite positioning system measurements, to reduce the systematic bias errors. A scale factor is applied to an estimated velocity of the swimmer's body to estimate the velocity of a mobile device on the swimmer's wrist, e.g., while above water.

Techniques are provided for determining a moving body's position and velocity in the presence of motion of a measuring device relative to the body. For example, a swimmer's position and velocity may be determined by compensating for bias that may result from a swimmer's arm swing. This may help avoid over-estimating a swimmer's velocity that results in inaccurate position estimation along the swimmer's path. To compensate for the swimmer's arm swing, an estimate of translational velocity due to arm rotation may be removed, e.g., from pseudo-range rates (PRRs) from satellite positioning system measurements, to reduce the systematic bias errors. A scale factor is applied to an estimated velocity of the swimmer's body to estimate the velocity of a mobile device on the swimmer's wrist, e.g., while above water.

An optical motion detecting device for a flight vehicle includes a base, an optical motion sensor and an operating processor. The optical motion sensor is disposed on the base and adapted to capture a plurality of frames. The operating processor is electrically connected with the optical motion sensor. The operating processor analyzes a pattern within the plurality of frames to acquire displacement of the base relative to a reference plane according to a known height value, and the known height value represents a height that the flight vehicle starts to move.

Systems and methods for determining a velocity of a fluid or an object are described. Systems and methods include receiving image data of the fluid or the object, the image data comprising a plurality of frames. Each frame comprises an array of pixel values. Systems and methods include creating a frame difference by subtracting an array of pixel values for a first frame of the image data from an array of pixel values for a second frame of the image data. Systems and methods include measuring a difference between a location of the object in the first frame of the image data and the second frame of the image data. Systems and methods include creating a correlation matrix based on the measured difference. Systems and methods include using the frame difference and the correlation matrix to automatically determine the velocity of the fluid or the object.

A method for tracking movement and turning angle of a mobile robotic device using two optoelectronic sensors positioned on the underside thereof. Digital image correlation is used to analyze images captured by the optoelectronic sensors and determine the amount of offset, and thereby amount of movement of the device. Trigonometric analysis of a triangle formed by lines between the positions of the optoelectronic sensors at different intervals may be used to determine turning angle of the mobile robotic device.

A method for tracking movement and turning angle of a mobile robotic device using two optoelectronic sensors positioned on the underside thereof. Digital image correlation is used to analyze images captured by the optoelectronic sensors and determine the amount of offset, and thereby amount of movement of the device. Trigonometric analysis of a triangle formed by lines between the positions of the optoelectronic sensors at different intervals may be used to determine turning angle of the mobile robotic device.

An optical motion detecting device for a flight vehicle includes a base, an optical motion sensor and an operating processor. The optical motion sensor is disposed on the base and adapted to capture a plurality of frames. The operating processor is electrically connected with the optical motion sensor. The operating processor analyzes a pattern within the plurality of frames to acquire displacement of the base relative to a reference plane according to a known height value, and the known height value represents a height that the flight vehicle starts to move.

Techniques are provided for determining a moving body's position and velocity in the presence of motion of a measuring device relative to the body. For example, a swimmer's position and velocity may be determined by compensating for bias that may result from a swimmer's arm swing. This may help avoid over-estimating a swimmer's velocity that results in inaccurate position estimation along the swimmer's path. To compensate for the swimmer's arm swing, an estimate of translational velocity due to arm rotation may be removed, e.g., from pseudo-range rates (PRRs) from satellite positioning system measurements, to reduce the systematic bias errors. A scale factor is applied to an estimated velocity of the swimmer's body to estimate the velocity of a mobile device on the swimmer's wrist, e.g., while above water.