Systems and techniques are described herein for performing optical flow estimation for one or more frames. For example, a process can include determining an optical flow prediction associated with a plurality of frames. The process can include determining a position of at least one feature associated with a first frame and determining, based on the position of the at least one feature in the first frame and the optical flow prediction, a position estimate of a search area for searching for the at least one feature in a second frame. The process can include determining, from within the search area, a position of the at least one feature in the second frame

A method may include obtaining first sensor data captured by a first sensor system and second sensor data captured by a second sensor system of a different type from the first sensor system. The method may include detecting a first object included in the first sensor data and a second object included in the second sensor data. The method may include assigning a first label to the first object and a second label to the second object after comparing the first and the second sensor data. The first and second labels may indicate degrees to which the first and the second objects match. Responsive to the first and second labels indicating that the first and the second objects match, the method may include designating a matched object representative of the first object and the second object and sending the matched object to a downstream computing system of an autonomous vehicle.

A method may include obtaining first sensor data captured by a first sensor system and second sensor data captured by a second sensor system of a different type from the first sensor system. The method may include detecting a first object included in the first sensor data and a second object included in the second sensor data. The method may include assigning a first label to the first object and a second label to the second object after comparing the first and the second sensor data. The first and second labels may indicate degrees to which the first and the second objects match. Responsive to the first and second labels indicating that the first and the second objects match, the method may include designating a matched object representative of the first object and the second object and sending the matched object to a downstream computing system of an autonomous vehicle.

A position estimation method for a tracking target is implemented in an unmanned aerial vehicle. The position estimation method include: estimating a target position of the tracking target at the next time according to an initial position of the tracking target at the current moment; determining an estimated width and an estimated height of the tracking target in an image captured by a pan-tilt-zoom camera of the unmanned aerial vehicle according to the estimated target position; obtaining an actual width and an actual height of the tracking target in the image; determining a height difference between the estimated width and the estimated height and a width difference between the actual height and the actual width; and updating the target position of the tracking target at the next time according to the height difference and the width difference.

A position estimation method for a tracking target is implemented in an unmanned aerial vehicle. The position estimation method include: estimating a target position of the tracking target at the next time according to an initial position of the tracking target at the current moment; determining an estimated width and an estimated height of the tracking target in an image captured by a pan-tilt-zoom camera of the unmanned aerial vehicle according to the estimated target position; obtaining an actual width and an actual height of the tracking target in the image; determining a height difference between the estimated width and the estimated height and a width difference between the actual height and the actual width; and updating the target position of the tracking target at the next time according to the height difference and the width difference.

In implementations of systems for estimating three-dimensional trajectories of physical objects, a computing device implements a three-dimensional trajectory system to receive radar data describing millimeter wavelength radio waves directed within a physical environment using beamforming and reflected from physical objects in the physical environment. The three-dimensional trajectory system generates a cloud of three-dimensional points based on the radar, each of the three-dimensional points corresponds to a reflected millimeter wavelength radio wave within a sliding temporal window. The three-dimensional points are grouped into at least one group based on Euclidean distances between the three-dimensional points within the cloud. The three-dimensional trajectory system generates an indication of a three-dimensional trajectory of a physical object corresponding to the at least one group using a Kalman filter to track a position and a velocity a centroid of the at least one group in three-dimensions.

In implementations of systems for estimating three-dimensional trajectories of physical objects, a computing device implements a three-dimensional trajectory system to receive radar data describing millimeter wavelength radio waves directed within a physical environment using beamforming and reflected from physical objects in the physical environment. The three-dimensional trajectory system generates a cloud of three-dimensional points based on the radar, each of the three-dimensional points corresponds to a reflected millimeter wavelength radio wave within a sliding temporal window. The three-dimensional points are grouped into at least one group based on Euclidean distances between the three-dimensional points within the cloud. The three-dimensional trajectory system generates an indication of a three-dimensional trajectory of a physical object corresponding to the at least one group using a Kalman filter to track a position and a velocity a centroid of the at least one group in three-dimensions.

Provided is a robot including: a chassis; wheels; electric motors; a network card; sensors; a processor; and a tangible, non-transitory, machine readable medium storing instructions that when executed by the processor effectuates operations including: capturing, with at least one exteroceptive sensor, a first image and a second image; determining, with the processor, an overlapping area of the first image and the second image by comparing the raw pixel intensity values of the first image to the raw pixel intensity values of the second image; combining, with the processor, the first image and the second image at the overlapping area to generate a digital spatial representation of the environment; and estimating, with the processor using a statistical ensemble of simulated positions of the robot, a corrected position of the robot to replace a last known position of the robot within the digital spatial representation of the environment.

The present application discloses a positioning method for a movable platform, including: detecting, by a laser positioning system (LPS) mounted on the movable platform, a plurality of reflectors mounted on a target object, wherein the movable platform is moving; calculating in real-time, by the LPS, according to the current position information, relative positions of the plurality of reflectors with respect to the LPS; and obtaining, by the LPS, a relative position of the movable platform with respect to the target object based on the relative positions of the plurality of reflectors with respect to the LPS. The present application also discloses positioning system that performs the positioning method.

The present application discloses a positioning method for a movable platform, including: detecting, by a laser positioning system (LPS) mounted on the movable platform, a plurality of reflectors mounted on a target object, wherein the movable platform is moving; calculating in real-time, by the LPS, according to the current position information, relative positions of the plurality of reflectors with respect to the LPS; and obtaining, by the LPS, a relative position of the movable platform with respect to the target object based on the relative positions of the plurality of reflectors with respect to the LPS. The present application also discloses positioning system that performs the positioning method.