Sensormatic Electronics Corporation

Locus Robotics Corporation

Changchun Li

Ian Christopher Westmacott

Mirko Ristivojevic

Matthew A Gruenke

Michael Sussman

Hian Kai Kwa

Seth Edwards Allen

Brad Edward Fiore

Keegan Burgess Smith

Scott Matthew Rydbeck

Rafael Gregorio Chavez

Stephen V Williams

A system for determining pose of a lidar sensor in an environment in order to calibrate the lidar sensor. The system includes at least two calibration boards, each having a first edge and a second edge. There is a controller coupled to the lidar sensor to cause the lidar sensor to direct a lidar scan at the calibration boards. The controller causes the lidar sensor to receive a reflection of the lidar scan from the calibration boards and determine locations of a first crossing point on the first edge and a second crossing point on the second edge of the calibration boards. The controller determines a reference plane defined by the first and second crossing points of each of the calibration boards, performs a plane transform of the reference frame to obtain a lidar sensor plane and determine from the lidar sensor plane a pose of the lidar sensor.

Calibration of a lidar sensor

A method for estimating a pose of a robot using two co-planar points on an object plane in the environment and two co-planar lines on the object plane, includes capturing with a camera on the robot an image of the object in the environment, including two observed points corresponding to the two co-planar points on the object and two observed lines corresponding to the two co-planar lines on the object; projecting onto the image plane the two co-planar points to obtain two projected points and projecting the two co-planar lines to obtain two projected lines; determining a point projection error by comparing the two projected co-planar points to corresponding observed points; determining a line projection error by comparing the two projected co-planar lines to corresponding observed lines; and estimating a current robot pose if the point projection error and the line projection error are below a predetermined error threshold.

Visual robot pose estimation

Robot charging dock includes a charge connector configured to mate with a charging port of a mobile robot. There is a charge connector frame having a front surface on which the charge connector is mounted. The front surface has a first side edge and a second side edge. There is a front cover disposed over the charge connector frame which has an aperture through which the charge connector protrudes. At least a portion of the front cover is spaced from the front surface of the charge connector frame, defining an internal region. There is an opening to the internal region formed along at least a portion of a perimeter of the aperture and there is a light source disposed in the internal region. The light source is directed toward the opening to allow the light source to illuminate charge connector.

Robot charging dock with illuminated charge connector

A method for rolling shutter compensation for a camera sensor mounted on a moving vehicle includes estimating, based on a plurality of images of an object, a speed and a direction of movement of the vehicle; acquiring an additional image of the object having four corners; estimating a location of each of the four corners of the object in an image plane defined by the additional image; determining a corrected location in 3D space for each of the four corners of the object; determining a first compensated location for each of the four corners of the object in the image plane; determining a second compensated location for each of the four corners of the object in the image plane; and determining a difference between the first compensated locations of the four corners of the object and the second compensated locations of the four corners of the object.

Rolling shutter compensation for moving digital optical camera sensors

A system and method for analysing queues in frames of video enables operators to preferably draw three regions of interest overlaid upon the video as short, medium, and long queue regions that form a notional queue area within the video. The regions are drawn with knowledge of, or in anticipation of, foreground objects such as individuals and vehicles waiting for service in a queue. Examples include retail point of sale locations or for automated teller machine (ATM) transactions. In conjunction with a video analytics system that analyses the movement of the foreground objects relative to the queue regions, the system determines the number of objects occupying each queue region, length of the queue, and other queue-related statistics. The system can then create reports and send messages that include the queue analysis results for directing operators to change their staffing resources as part of a real-time queue servicing and optimization response.

Method and system for queue length analysis

A system and method for analyzing queues in frames of video enables operators to preferably draw three regions of interest overlaid upon the video as short, medium, and long queue regions that form a notional queue area within the video. The regions are drawn with knowledge of, or in anticipation of, foreground objects such as individuals and vehicles waiting for service in a queue. Examples include retail point of sale locations or for automated teller machine (ATM) transactions. In conjunction with a video analytics system that analyses the movement of the foreground objects relative to the queue regions, the system determines the number of objects occupying each queue region, length of the queue, and other queue-related statistics. The system can then create reports and send messages that include the queue analysis results for directing operators to change their staffing resources as part of a real-time queue servicing and optimization response.

A method and system for analyzing video data in a security system. An analysis compares a current frame to a background model. The analysis system compares the background model to the current frame to identify changed pixel patches. The analysis system uses morphological image processing to generate masks based on the changed pixel patches. Next, the analysis system applies the masks to the background model and the current frames to determine whether the changed pixel patches are characteristic of abandoned or removed objects within the video data.

Method and system to characterize video background changes as abandoned or removed objects

A system and method for analyzing queues in frames of video enables operators to preferably draw three regions of interest overlaid upon the video as short, medium, and long queue regions that form a notional queue area within the video. The regions are drawn with knowledge of, or in anticipation of, foreground objects such as individuals and vehicles waiting for service in a queue. Examples include retail point of sale locations or for automated teller machine (ATM) transactions. In conjunction with a video analytics system that analyzes the movement of the foreground objects relative to the queue regions, the system determines the number of objects occupying each queue region, length of the queue, and other queue-related statistics. The system can then create reports and send messages that include the queue analysis results for directing operators to change their staffing resources as part of a real-time queue servicing and optimization response.

Growing community of inventors

Concord, MA, United States of America

Changchun Li