Methods, apparatuses and computer program products for depalletizing mixed objects
Methods, apparatuses, systems, computing devices, and/or the like are provided. An example method may include receiving, from a perception subsystem associated with an object depalletization system, first imaging data associated with a plurality of objects disposed on a pallet; calculate, based at least in part on the first imaging data, one or more comparative dimension measures associated with the plurality of objects; determine whether the one or more comparative dimension measures satisfy a comparative dimension threshold range; and in response to determining that the one or more comparative dimension measures satisfy the comparative dimension threshold range, cause an execution subsystem associated with the object depalletization system to operate in a constant pallet mode.
1 . An apparatus associated with an object depalletization system, the apparatus comprising at least one processor and at least one non-transitory memory comprising a computer program code, the at least one non-transitory memory and the computer program code configured to, with the at least one processor, cause the apparatus to:
receive, from a perception subsystem associated with the object depalletization system, first imaging data associated with a plurality of objects disposed on a pallet;
calculate, based at least in part on the first imaging data, one or more comparative dimension measures associated with the plurality of objects;
determine whether the one or more comparative dimension measures satisfy a comparative dimension threshold range; and
in response to determining that the one or more comparative dimension measures satisfy the comparative dimension threshold range, transmit control instructions to cause an execution subsystem comprising a depalletizer device associated with the object depalletization system to operate in a constant pallet mode in which all objects on a top layer of the pallet are depalletized with the apparatus using same settings for the depalletizer device; and
transmit control instructions to the execution subsystem to end the constant pallet mode when an object height difference between a first object and a second object of the plurality of objects in the same top layer of the pallet is not within a height difference threshold range, wherein height of the first object and the second object of the plurality of objects is received from the execution subsystem associated with the object depalletization system.
2 . The apparatus of claim 1 , wherein the perception subsystem comprises a two dimensional (2-D) image capturing device, wherein the first imaging data comprises 2-D image data associated with the plurality of objects and captured by the 2-D image capturing device.
3 . The apparatus of claim 1 , wherein the perception subsystem comprises a three dimensional (3-D) image capturing device, wherein the first imaging data comprises 3-D image data associated with the plurality of objects and captured by the 3-D image capturing device.
4 . The apparatus of claim 1 , wherein, prior to calculating the one or more comparative dimension measures associated with the plurality of objects, the at least one non-transitory memory and the computer program code are configured to, with the at least one processor, cause the apparatus to:
input the first imaging data to an object segmentation machine learning model, wherein the first imaging data comprises at least one of 2-D image data associated with the plurality of objects; and
receive, from the object segmentation machine learning model, a plurality of object segmentation indications associated with the at least one of 2-D image data.
5 . The apparatus of claim 4 , wherein calculating the one or more comparative dimension measures is based at least in part on the plurality of object segmentation indications.
6 . The apparatus of claim 1 , wherein, when calculating the one or more comparative dimension measures associated with the plurality of objects, the at least one non-transitory memory and the computer program code are configured to, with the at least one processor, cause the apparatus to:
determine, based at least in part on 2-D image data or 3-D image data from the perception subsystem, a first image-dimension measure associated with the first object;
determine, based at least in part on the 2-D image data or the 3-D image data from the perception subsystem, a second image-dimension measure associated with the second object; and
determine the one or more comparative dimension measures based at least in part on the first image-dimension measure and the second image-dimension measure.
7 . A computer-implemented method comprising:
receiving, from a perception subsystem associated with an object depalletization system, first imaging data associated with a plurality of objects disposed on a pallet;
calculating, based at least in part on the first imaging data, one or more comparative dimension measures associated with the plurality of objects;
determining whether the one or more comparative dimension measures satisfy a comparative dimension threshold range; and
in response to determining that the one or more comparative dimension measures satisfy the comparative dimension threshold range, transmitting control instructions to cause an execution subsystem comprising a depalletizer device associated with the object depalletization system to operate in a constant pallet mode in which all objects on a top layer of the pallet are depalletized using same settings for the depalletizer device; and
transmitting control instructions to the execution subsystem to end the constant pallet mode when an object height difference between a first object and a second object of the plurality of objects in the same top layer of the pallet is not within a height difference threshold range, wherein height of the first object and the second object of the plurality of objects is received from the execution subsystem associated with the object depalletization system.
8 . The computer-implemented method of claim 7 , wherein the perception subsystem comprises a two dimensional (2-D) image capturing device, wherein the first imaging data comprises 2-D image data associated with the plurality of objects and captured by the 2-D image capturing device.
9 . The computer-implemented method of claim 7 , wherein the perception subsystem comprises a three dimensional (3-D) image capturing device, wherein the first imaging data comprises 3-D image data associated with the plurality of objects and captured by the 3-D image capturing device.
10 . The computer-implemented method of claim 7 , wherein, prior to calculating the one or more comparative dimension measures associated with the plurality of objects, the computer-implemented method further comprises:
inputting the first imaging data to an object segmentation machine learning model, wherein the first imaging data comprises at least one of 2-D image data associated with the plurality of objects; and
receiving, from the object segmentation machine learning model, a plurality of object segmentation indications associated with the at least one of 2-D image data.
11 . The computer-implemented method of claim 10 , wherein calculating the one or more comparative dimension measures is based at least in part on the plurality of object segmentation indications.
12 . The computer-implemented method of claim 7 , wherein, when calculating the one or more comparative dimension measures associated with the plurality of objects, the computer-implemented method further comprises:
determining, based at least in part on 2-D image data or 3-D image data from the perception subsystem, a first image-dimension measure associated with the first object;
determining, based at least in part on the 2-D image data or the 3-D image data from the perception subsystem, a second image-dimension measure associated with the second object; and
determining the one or more comparative dimension measures based at least in part on the first image-dimension measure and the second image-dimension measure.
13 . A computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising an executable portion configured to:
receive, from a perception subsystem associated with an object depalletization system, first imaging data associated with a plurality of objects disposed on a pallet;
calculate, based at least in part on the first imaging data, one or more comparative dimension measures associated with the plurality of objects;
determine whether the one or more comparative dimension measures satisfy a comparative dimension threshold range; and
in response to determining that the one or more comparative dimension measures satisfy the comparative dimension threshold range, transmit control instructions to cause an execution subsystem comprising a depalletizer device associated with the object depalletization system to operate in a constant pallet mode in which all objects on a top layer of the pallet are depalletized using same settings for the depalletizer device; and
transmit control instructions to the execution subsystem to end the constant pallet mode when an object height difference between a first object and a second object of the plurality of objects in the same top layer of the pallet is not within a height difference threshold range, wherein height of the first object and the second object of the plurality of objects is received from the execution subsystem associated with the object depalletization system.
14 . The computer program product of claim 13 , wherein the perception subsystem comprises a two dimensional (2-D) image capturing device, wherein the first imaging data comprises 2-D image data associated with the plurality of objects and captured by the 2-D image capturing device.
15 . The computer program product of claim 13 , wherein the perception subsystem comprises a three dimensional (3-D) image capturing device, wherein the first imaging data comprises 3-D image data associated with the plurality of objects and captured by the 3-D image capturing device.
16 . The computer program product of claim 13 , wherein, prior to calculating the one or more comparative dimension measures associated with the plurality of objects, the computer-readable program code portions comprise the executable portion configured to:
input the first imaging data to an object segmentation machine learning model, wherein the first imaging data comprises at least one of 2-D image data associated with the plurality of objects; and
receive, from the object segmentation machine learning model, a plurality of object segmentation indications associated with the at least one of 2-D image data.
17 . The computer program product of claim 16 , wherein calculating the one or more comparative dimension measures is based at least in part on the plurality of object segmentation indications.
18 . The apparatus of claim 1 , wherein the execution subsystem further comprises a height sensing device, and wherein the at least one non-transitory memory and the computer program code are configured to, with the at least one processor, cause the apparatus to:
receive, from the height sensing device, a first height data associated with the first object;
determine a lift height parameter associated with the depalletizer device in the constant pallet mode based at least in part on the first height data; and
cause the depalletizer device to lift one or more objects from the plurality of objects other than the first object to a same lift height based at least in part on the lift height parameter when the execution subsystem is in the constant pallet mode.
19 . The computer-implemented method of claim 7 , further comprising:
receiving, from a height sensing device, a first height data associated with the first object;
determining a lift height parameter associated with the depalletizer device in the constant pallet mode based at least in part on the first height data; and
causing the depalletizer device to lift one or more objects from the plurality of objects other than the first object to a same lift height based at least in part on the lift height parameter when the execution subsystem is in the constant pallet mode.
20 . The computer program product of claim 13 , wherein the execution subsystem further comprises a height sensing device, and wherein the executable portion is further configured to:
receive, from the height sensing device, a first height data associated with the first object;
determine a lift height parameter associated with the depalletizer device in the constant pallet mode based at least in part on the first height data; and
cause the depalletizer device to lift one or more objects from the plurality of objects other than the first object to a same lift height based at least in part on the lift height parameter when the execution subsystem is in the constant pallet mode.