The present disclosure discloses a point cloud-based map calibration method and system, a robot and a cloud platform. The method is applied to a cloud platform communicatively connected to a designated robot, and includes: obtaining environmental acquisition information from the designated robot; performing three-dimensional point cloud reconstruction on the environmental acquisition information, performing obstacle recognition on a three-dimensional point cloud reconstruction result, and obtaining an obstacle recognition result including obstacle information and confidence information corresponding to the obstacle information; and when it is determined that the confidence information satisfies a first preset index, sending map calibration information corresponding to the obstacle information to the designated robot, so that the designated robot calibrates map information according to the map calibration information.

Some aspects relate to an apparatus, method and/or system of radar tracking. For example, a radar tracker may be configured to generate target tracking information corresponding to a plurality of targets in an environment of a radar device. For example, the radar tracker may include a processor configured to determine the target tracking information based on a plurality of multi-target density functions corresponding to a respective plurality of target types, and to update the plurality of multi-target density functions based on detection information corresponding to a plurality of detections in the environment. For example, the radar tracker may include an output to output the target tracking information.

For example, a radar apparatus may include a processor configured to generate radar information based on input radar data, the input radar data based on radar signals of a Multiple-Input-Multiple-Output (MIMO) radar antenna, wherein the processor is configured to generate the radar information by calibrating an antenna Mismatch (MM) of the MIMO radar antenna in a first dimension of an Azimuth-Elevation domain according to a plurality of one-dimensional (1D) Inverse Coupling Matrices (ICMs), the plurality of 1D ICMs corresponding to a plurality of antenna sub-arrays of the MIMO radar antenna and to a plurality of angles in a second dimension of the Azimuth-Elevation domain.

A robot system is provided that includes movable parts, one or more object detecting sensors, and one or more processors, wherein the one or more object detecting sensors is dispose at or near the elbow, the wrist, or the position between the elbow and the wrist of the robot. Multiple embodiments are introduced for the implementation of the object detection of the robot system.

A system for monitoring and improving social agent interaction quality includes a computing platform having processing hardware and a system memory storing a software code. The processing hardware is configured to execute the software code to receive, from a social agent, interaction data describing an interaction of the social agent with a user, and to perform an assessment of the interaction, using the interaction data, as one of successful or including a flaw. When the assessment indicates that the interaction includes the flaw, the processing hardware is further configured to execute the software code to identify an interaction strategy for correcting the flaw, and to deliver, to the social agent, one or both of the assessment and the interaction strategy to correct the flaw in the interaction.

A mobile robot is configured for operation in a commercial or industrial setting, such as an office building or retail store. The robot can patrol one or more routes within a building, and can detect violations of security policies by objects, building infrastructure and security systems, or individuals. In response to the detected violations, the robot can perform one or more security operations. The robot can include a removable fabric panel, enabling sensors within the robot body to capture signals that propagate through the fabric. In addition, the robot can scan RFID tags of objects within an area, for instance coupled to store inventory. Likewise, the robot can generate or update one or more semantic maps for use by the robot in navigating an area and for measuring compliance with security policies.

Embodiments of the present disclosure relate to generating RADAR (RAdio Detection And Ranging) point clouds based on RADAR data obtained from one or more RADAR sensors disposed on one or more ego-machines. In these or other embodiments, the RADAR point clouds may be used to generate map data. Additionally or alternatively, the RADAR point clouds may be used for performing localization.

Data from a radar sensor (502) moving through a static environment may be smoothed and used to generate range profiles by approximating peaks. A direction of arrival (DOA) can then be determined based on the range profile in order to generate a reprojection map. The reprojection map is used to provide updates to a stored map in a robot (102).

A method of determining the location of the first object (10) may include receiving signals at a second object (20) from a plurality of measurement points (11) on the first object (10), estimating locations of the plurality of measurement points (11) on the first object (10), determining an estimate of a location of the first object (10), determining a first measurement of an orientation of the first object (10) based on the estimating of the locations of the plurality of measurement points (11) on the first object (10), and determining a second measurement of the orientation of the first object (10) based on measurements by an orientation sensor (12) on the first object (10). The method may include estimating an error of the estimate of the location of the first object (10) based on a difference between the first and second orientation measurements and adjusting a movement of the second object (20) based on the estimated error.

A robotic work tool system (200) comprising a robotic worktool (100) comprising a distance sensor (190, 190′, 190″), the robotic work tool (100) being configured to determine a sensed distance (SD) to a surface travelled (G); determine whether the sensed distance is greater than a threshold distance; and if so detect a lift event.