Technologies Holdings Corporation

Transocean Sedco Forex Ventures Limited

Bradley J Prevost

Mark Alan Foresman

Peter Willem Van Der Sluis

Alireza Janani

Marijn Van Aart

Marinus P Van Aart

Charles Blakely

A processor is operably coupled to a time of flight (TOF) camera, a light detection and ranging (LIDAR) sensor, and an optical camera. The processor can receive a TOF signal representative of a first coordinate associated with a stick-up height of a tool joint of a pipe of a drill string during a tripping operation on a rig drill floor, and a pitch and a roll of the tool joint. The processor can receive a LIDAR signal representative of a second coordinate associated with the stick-up height, and the pitch of the tool joint. The processor can receive an optical camera signal representative of a third coordinate associated with the stick-up height of the tool joint and the roll of the tool joint. The processor can generate a pose estimate and an orientation estimate based on the signals.

Systems, methods and apparatus for characterizing stick-up height, position and orientation of a drill pipe

A leg () detection system comprising: a robotic arm () comprising a gripping portion () for holding a teat cup () for attaching to a teat (S, 203) of a dairy livestock (); an imaging system coupled to the robotic arm () and configured to capture a first three-dimensional (3D) image () of a rearview of the dairy livestock () in a stall (), the imaging system comprising a 3D camera () or a laser (), wherein each pixel of the first 3D image () is associated with a depth value; one or more memory () devices configured to store a reference (3D) 3D image () of the stall () without any dairy livestock (); and a processor () communicatively coupled to the imaging system and the one or more memory () devices, the processor () configured to: access the first 3D image () and the reference (3D) 3D image (); subtract the first 3D image () from the reference (3D) 3D image () to produce a second 3D image (); perform morphological image () processing on the second 3D image () to produce a third 3D image (); perform image () thresholding on the third 3D image () to produce a fourth 3D image (); cluster () data from the fourth 3D image (); identify, using the clustered data from the fourth 3D image (), one or more legs () of the dairy livestock (); and provide instructions for movements of the robotic arm () to avoid the identified one or more legs () while attaching the teat cup () to the teat (S,) of the dairy livestock ().

Vision system for leg detection

A system that includes a robotic arm, a laser, a memory, and a processor. The processor is configured to position the laser adjacent to a dairy livestock and to modify teat location information for one or more teats of the dairy livestock based on a robot position offset between the dairy livestock and the robotic arm. The processor is further configured to generate a teat position associated with an unknown teat based on a scan of the dairy livestock and to determine a position distances between the teat position and teats of the dairy livestock. The processor is further configured to identify a teat of the dairy livestock with the smallest position distance, to associate a teat identifier for the unknown teat with the identified teat, and to store the association in the memory.

Vision system with teat identification

A system that includes a robotic arm, a laser, a three-dimensional (3D) camera, and a processor. The processor is configured to send instructions to position the robotic arm adjacent to a dairy livestock, to send a signal that initiates scanning a portion of the dairy livestock, and to generate teat candidate position information based on the scan of the dairy livestock. The processor is further configured receive target teat information, identify a teat candidate within a teat location range of the target teat, and link the identified teat candidate with a teat identifier. The processor is further configured to send instructions to the robotic arm to move at least a portion of the robotic arm toward the target teat based on the teat candidate position information for the identified teat candidate that is linked with the teat identifier.

Vision system with teat candidate identification

A system that includes a laser configured to generate a profile signal of at least a portion of a dairy livestock and a processor. The processor is configured to obtain the profile signal and detect one or more edge pair candidates in the profile signal, compare the complementary distance gradients of each of the one or more edge pair candidates to a minimum distance gradient length to be considered an edge pair, and identify an edge pair from among the one or more edge pair candidates as a teat candidate based on the comparison. The processor is further configured to determine position information for the teat candidate.

Vision system with teat detection

A leg () detection system comprising: a robotic arm () comprising a gripping portion () for holding a teat cup () for attaching to a teat () of a diary livestock (); an imaging system coupled to the robotic arm () and configured to capture a first three-dimensional (3D) image () of a rearview of the dairy livestock () in a stall (), the imaging system comprising a 3D camera () or a laser (), wherein each pixel of the first 3D image () is associated with a depth value; one or more memory () devices configured to store a reference (3D) 3D image () of the stall () without any dairy livestock (); and a processor () communicatively coupled to the imaging system and the one or more memory () devices, the processor () configured to: access the first 3D image () and the reference (3D) 3D image (); subtract the first 3D image () from the reference (3D) 3D image () to produce a second 3D image (); perform morphological image () processing on the second 3D image () to produce a third 3D image (); perform image () thresholding on the third 3D image () to produce a fourth 3D image (); cluster () data from the fourth 3D image (); identify, using the clustered data from the fourth 3D image () to avoid the identified one or more legs () while attaching the teat cup () to the teat (S,) of the dairy livestock ().

Vision system for teat detection

A system includes a robotic arm, a laser, and a processor. The processor is configured to command the robotic arm to move to a location of an expected teat position of a dairy livestock and to command the laser to perform two scans of the dairy livestock. The processor is further configured to determine whether a first teat is found in both of the scans, and if so, determine whether locations of the first teat in the two scans are within a predetermined distance of each other. The processor is further configured to, in response to determining that locations of the first teat in the two scans are within the predetermined distance of each other, command the robotic arm to move to a location corresponding to the location of the first teat and to command the robotic arm to attach a teat cup to the first teat.

A system that includes a three-dimensional (3D) camera configured to capture a 3D image of a rearview of a dairy livestock in a stall and a processor. The processor is configured to obtain the 3D image, identify one or more regions within the 3D image comprising depth values greater than a depth value threshold, and s to identify a thigh gap region from the one or more regions. The processor is further configured to demarcate an access region within the thigh gap region and demarcate a tail detection region. The processor is further configured to identify one or more tail candidates within the tail detection region, to identify a tail candidate that corresponds with a tail model as the tail, and to determine position information for the tail.

Vision system with tail detection

A robotic arm maneuvers a teat preparation cup and executes instructions from a robotic arm controller. The controller comprises an interface, a memory, and a processor. The processor instructs the sensor to perform a first scan. If the first scan discovers a first set of teats, the processor moves the robotic arm a first distance and instructs the sensor to perform a second scan. If the second scan discovers a second set of teats, the processor moves the robotic arm to a location under the first teat, and instructs the sensor to perform a third scan. The processor determines if the third scan discovers a third set of teats. If each of the first set, second set, and third set of discovered teats comprises the first teat, the processor instructs the robotic arm to attach the preparation cup to the first teat.

System and method for preparation cup attachment

A system that includes a three-dimensional (3D) camera configured to capture a 3D image of a rearview of a dairy livestock in a stall, a memory, and a processor. The processor is configured to obtain the 3D image, identify one or more regions within the 3D image comprising depth values greater than a depth value threshold, and apply the thigh gap detection rule set to the one or more regions to identify a thigh gap region. The processor is further configured to demarcate an access region within the thigh gap region and demarcate a tail detection region. The processor is further configured to partition the 3D image within the tail detection region to generate a plurality of image depth planes, examine each of the plurality of image depth planes, and determine position information for the tail of the dairy livestock in response to identifying the tail of the dairy livestock.

A system that includes a laser, a three-dimensional (3D) camera, a memory, and a processor. The processor is configured to determine the position of a first teat candidate relative to a second teat candidate, assign the first teat candidate and the second teat candidate as a left teat candidate or right teat candidate, and receive a teat identifier for a target teat. The processor is configured to determine whether the left or right teat candidate is within a teat location range of the target teat and to link the teat identifier with the left teat candidate or right teat candidate based on the determination.

A system that includes a laser, a memory, and a processor. The processor is configured to receive a teat position associated with an unknown teat, determine a first position distance between the teat position and a first teat, determine a second position distance between the teat position and a second teat, determine a third position distance between the teat position and a third teat, and determine a fourth position distance between the teat position and a fourth teat. The processor is further configured to compare the first position distance, the second position distance, the third position distance, and the fourth position distance to determine a smallest position distance from the unknown teat, identify a teat of the dairy livestock corresponding with the smallest position distance, associate a teat identifier for the unknown teat with the identified teat, and store the association in the memory.

A system that includes a laser configured to generate a profile signal of at least a portion of a dairy livestock, a memory operable to store a teat detection rule set, and a processor. The processor is configured to obtain the profile signal and detect one or more edge pair candidates in the profile signal, compare the complementary distance gradients of each of the one or more edge pair candidates to a minimum distance gradient length to be considered an edge pair, and identify one or more edge pairs from among the one or more edge pair candidates based on the comparison. The processor is further configured to apply the teat detection rule set to the one or more edge pairs to identify one or more teat candidates from among the one or more edge pairs and determine position information for the one or more teat candidates.

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Pearland, TX, United States of America

Bradley J Prevost