VACUUM-BASED END EFFECTOR, SYSTEM, AND METHOD FOR DETECTING PARCEL ENGAGEMENT AND CLASSIFYING PARCELS USING AUDIO

1 . A method for classifying parcels, comprising steps of:

processing, by a processor, audio data received from one or more microphones, the audio data corresponding to a robot engaging a parcel; and

classifying, by the processor, the parcel as a particular parcel type based on the audio data corresponding to the robot engaging the parcel.

2 . The method as recited in claim 1 , wherein classifying the parcel includes a step of inputting the audio data corresponding to the robot engaging the parcel into an audio classifier model configured to identify parcel type based on audio data.

3 . The method as recited in claim 2 ,

wherein the audio data corresponds to one or more vacuum cups of the robot engaging the parcel; and

wherein the audio classifier model is a neural network pre-trained on a collection of audio samples obtained by the one or more microphones, the collection of audio samples including audio samples corresponding to the one or more vacuum cups engaging a plurality of parcels of different types at different times.

4 . The method as recited in claim 3 , wherein the audio classifier model is a convolutional neural network.

5 . The method as recited in claim 1 , and further comprising at least one of:

a step of communicating, by the processor, instructions which cause the robot to transfer the parcel to one of multiple potential locations based on the particular parcel type the parcel is classified as; and

a step of communicating, by the processor, instructions which cause a movement speed of the robot to be reduced based on the particular parcel type the parcel is classified as.

6 . The method as recited in claim 1 , wherein the one or more microphones are positioned in proximity to one or more vacuum cups of a vacuum-based end effector of the robot to obtain the audio data corresponding to the one or more vacuum cups engaging the parcel.

7 . The method as recited in claim 6 ,

wherein the one or more vacuum cups includes a plurality of vacuum cups; and

wherein the one or more microphones includes a microphone positioned between at least two vacuum cups of the plurality of vacuum cups.

8 . The method as recited in claim 6 ,

wherein the one or more vacuum cups includes a plurality of vacuum cups; and

wherein the one or more microphones includes a microphone centrally positioned relative to the plurality of vacuum cups.

9 . The method as recited in claim 6 ,

wherein the one or more vacuum cups includes a plurality of vacuum cups; and

wherein the one or more microphones is a single microphone positioned to obtain sound recordings of each of the plurality of vacuum cups as the plurality of vacuum cups engage the parcel.

10 . A method for classifying parcels, comprising steps of:

positioning one or more microphones in proximity to one or more vacuum cups of a vacuum-based end effector of a robot to obtain audio data corresponding to the one or more vacuum cups engaging a parcel for transfer;

processing, by a processor, the audio data received from the one or more microphones; and

classifying, by the processor, the parcel as a particular parcel type based on the audio data.

11 . The method as recited in claim 10 , wherein classifying the parcel includes a step of inputting the audio data into an audio classifier model configured to identify parcel type based on audio data.

12 . The method as recited in claim 11 , wherein the audio classifier model is a neural network pre-trained on a collection of audio samples obtained by the one or more microphones, the collection of audio samples including audio samples corresponding to the one or more vacuum cups engaging a plurality of parcels of different types at different times.

13 . The method as recited in claim 12 , wherein the audio classifier model is a convolutional neural network.

14 . The method as recited in claim 10 , and further comprising at least one of:

a step of communicating, by the processor, instructions which cause the robot to transfer the parcel to one of multiple potential locations based on the particular parcel type the parcel is classified as; and

a step of communicating, by the processor, instructions which cause a movement speed of the robot to be reduced based on the particular parcel type the parcel is classified as.

15 . A vacuum-based end effector, comprising:

a base plate with an upper surface configured for connection to a framework of a robot;

one or more vacuum cups connected to the base plate and configured to be placed in fluid communication with a vacuum source; and

one or more microphones configured to obtain audio data as the one or more vacuum cups engage a parcel, with each microphone of the one or more microphones positioned below the upper surface of the base plate and mounted to at least one of the base plate and the one or more vacuum cups.

16 . The vacuum-based end effector according to claim 15 , and further comprising:

a controller including a processor for executing instructions stored in a memory component to (i) receive and process the audio data obtained by the one or more microphones, with the audio data corresponding to the one or more vacuum cups engaging the parcel, and (ii) identify a characteristic of the parcel based on the audio data obtained by the one or more microphones.

17 . The vacuum-based end effector according to claim 15 ,

wherein the one or more vacuum cups includes a plurality of vacuum cups; and

wherein the one or more microphones includes a microphone centrally positioned relative to at least two vacuum cups of the plurality of vacuum cups.

18 . The vacuum-based end effector according to claim 15 ,

wherein the one or more vacuum cups includes a plurality of vacuum cups; and

wherein the one or more microphones is a single microphone mounted to the base plate in a central position relative to the plurality of vacuum cups.