Abstract: The method can include: determining image data; identifying a container using an object detector; and classifying a container state. The method can optionally include performing an action based on the container state classification. However, the method can additionally or alternatively include any other suitable elements. The method functions to detect and classify the state of bowls (i.e., complete/incomplete) to facilitate ingredient insertion into (unserved, ‘incomplete’) bowls along an assembly line.

Abstract: The system can include: a base structure, a set of support elements, and/or any other suitable components. The system can optionally include a foodstuff bin and a force sensor. However, the system can additionally or alternatively include any other suitable set of components. The system functions to facilitate refilling of ingredients within foodstuff bins and/or replacement of foodstuff bins. Additionally or alternatively, the system can function to facilitate repeatable positioning of foodstuff bins within a workspace of the robotic arm and/or a robotic assembly module. Additionally or alternatively, the system can function to facilitate rapid calibration, servicing, and/or cleaning of foodstuff assembly modules.

Abstract: The multi-deposit end effector system 100 can include: a set of actuators 110; an optional set of utensil mating connectors 120; and a plurality of utensils 200. Each utensil can include: a set of scoops 210; a set of mechanical linkages 220; a set of ingressive elements 230; and/or any other suitable components. However, system 100 can additionally or alternatively include any other suitable set of components. The system functions to facilitate ingredient (e.g., foodstuffs) manipulation with the plurality of utensils. More preferably, the system can function to facilitate portioned ingredient picking and/or deposition (e.g., insertion at a target foodstuff container and/or placement location) using each utensil of the plurality of utensils.

Abstract: An end effector system can include: an optional actuator; an optional utensil mating connector; and a utensil. The utensil can include: a set of scoops; a set of mechanical linkages; a set of ingressive elements; and/or any other suitable components. However, the end effector system can additionally or alternatively include any other suitable set of components. The end effector system functions to facilitate picking of ingredients (e.g., foodstuffs), ingredient transformation, and/or ingredient insertion (e.g., at a target foodstuff container and/or placement location) via a grasp cavity of the utensil. Additionally or alternatively, the end effector system can function to shape a profile of ingredients (e.g., upon insertion). Additionally or alternatively, the end effector system can function to evacuate ingredients from the grasp cavity (e.g., clearing out ingredients adhering to the utensil).

Abstract: The method can include: receiving sensor measurements; maintaining an ingredient model for a foodstuff bin; determining a set of ingredient parameters; providing feedback based on the ingredient parameters; and/or any other suitable elements. The method can optionally include determining a refill event; and responding to a refill event. However, the method can additionally or alternatively include any other suitable elements. The method can function to facilitate automatic refill notifications at a human-machine interface (HMI) and/or can function to facilitate automatic control adjustments based on ingredient refill events. Additionally or alternatively, the method can function to facilitate provision of user feedback for key ingredient parameters, such as a remaining ingredient amount in a particular foodstuff bin, pick weight/volume statistics, via the HMI.

Abstract: The method can include: sampling images of a conveyor region S110; determining a set of patches S120; estimating a displacement for each patch S130; estimating a conveyor motion parameter(s) based on the patch displacement S140; and optionally performing an action based on the conveyor motion parameter S150. However, the method S100 can additionally or alternatively include any other suitable elements. The method S100 functions to estimate a set of conveyor motion parameters (e.g., conveyor speed). Additionally or alternatively, the method can function to enable dynamic control of an independent robotic assembly system(s) to accommodate conveyor motion changes.

Abstract: The system can include an actuator; a set of links; and a foot. The automated stabilizer can optionally include a swivel (e.g., integrated into the foot); a support structure; and a wheel assembly. However, the automated stabilizer can additionally or alternatively include any other suitable set of components. The automated stabilizer preferably functions to at least partially support a robotic assembly module against an uneven floor surface. Additionally or alternatively, an automated stabilizer can function to enable (automatic) leveling of a robotic assembly system (e.g., aligning the vertical axis of the system with a weight vector).

Abstract: The method can include: determining image data; identifying a container using an object detector; and classifying a container state. The method can optionally include performing an action based on the container state classification. However, the method can additionally or alternatively include any other suitable elements. The method functions to detect and classify the state of bowls (i.e., complete/incomplete) to facilitate ingredient insertion into (unserved, ‘incomplete’) bowls along an assembly line.

Abstract: The multi-deposit end effector system 100 can include: a set of actuators 110; an optional set of utensil mating connectors 120; and a plurality of utensils 200. Each utensil can include: a set of scoops 210; a set of mechanical linkages 220; a set of ingressive elements 230; and/or any other suitable components. However, system 100 can additionally or alternatively include any other suitable set of components. The system functions to facilitate ingredient (e.g., foodstuffs) manipulation with the plurality of utensils. More preferably, the system can function to facilitate portioned ingredient picking and/or deposition (e.g., insertion at a target foodstuff container and/or placement location) using each utensil of the plurality of utensils.

Abstract: The method can include: receiving sensor measurements; maintaining an ingredient model for a foodstuff bin; determining a set of ingredient parameters; providing feedback based on the ingredient parameters; and/or any other suitable elements. The method can optionally include determining a refill event; and responding to a refill event. However, the method can additionally or alternatively include any other suitable elements. The method can function to facilitate automatic refill notifications at a human-machine interface (HMI) and/or can function to facilitate automatic control adjustments based on ingredient refill events. Additionally or alternatively, the method can function to facilitate provision of user feedback for key ingredient parameters, such as a remaining ingredient amount in a particular foodstuff bin, pick weight/volume statistics, via the HMI.

Abstract: The method can include: sampling images of a conveyor region S110; determining a set of patches S120; estimating a displacement for each patch S130; estimating a conveyor motion parameter(s) based on the patch displacement S140; and optionally performing an action based on the conveyor motion parameter S150. However, the method S100 can additionally or alternatively include any other suitable elements. The method S100 functions to estimate a set of conveyor motion parameters (e.g., conveyor speed). Additionally or alternatively, the method can function to enable dynamic control of an independent robotic assembly system(s) to accommodate conveyor motion changes.

Abstract: The system can include an actuator; a set of links; and a foot. The automated stabilizer can optionally include a swivel (e.g., integrated into the foot); a support structure; and a wheel assembly. However, the automated stabilizer can additionally or alternatively include any other suitable set of components. The automated stabilizer preferably functions to at least partially support a robotic assembly module against an uneven floor surface. Additionally or alternatively, an automated stabilizer can function to enable (automatic) leveling of a robotic assembly system (e.g., aligning the vertical axis of the system with a weight vector).

Abstract: The method S100 can include: providing bowls within the workspace based on the assembly context S105; sampling sensor data for the workspace S110; detecting bowls based on the sensor data S120; determining a labeled training dataset S130; and training a classifier for the assembly context S140. However, the method S100 can additionally or alternatively include any other suitable elements.

Abstract: The multi-deposit end effector system 100 can include: a set of actuators 110; an optional set of utensil mating connectors 120; and a plurality of utensils 200. Each utensil can include: a set of scoops 210; a set of mechanical linkages 220; a set of ingressive elements 230; and/or any other suitable components. However, system 100 can additionally or alternatively include any other suitable set of components. The system functions to facilitate ingredient (e.g., foodstuffs) manipulation with the plurality of utensils. More preferably, the system can function to facilitate portioned ingredient picking and/or deposition (e.g., insertion at a target foodstuff container and/or placement location) using each utensil of the plurality of utensils.

Abstract: A method can include: receiving imaging data; identifying containers using an object detector; scheduling insertion based on the identified containers; and optionally performing an action based on a scheduled insertion. However, the method can additionally or alternatively include any other suitable elements. The method functions to schedule insertion for a robotic system (e.g., ingredient insertion of a robotic foodstuff assembly module). Additionally or alternatively, the method can function to facilitate execution of a dynamic insertion strategy; and/or facilitate independent operation of a plurality of robotic assembly modules along a conveyor line.

Abstract: The system 100 can include a robotic assembly system 110 and a set of barriers 120. The robotic assembly system can include a robot arm, a frame, an optional utensil, an optional bin, and/or any other suitable components. However, the system 100 can additionally or alternatively include any other suitable set of components. The system 100 functions to facilitate robotic assembly of items/ingredients (e.g., in an assembly line environment). Additionally or alternatively, the system 100 can function to guard robotic assembly components during operation. Additionally or alternatively, the system 100 can function to mitigate the influence of a robotic assembly system on surrounding workers (e.g., in an assembly line environment).

Abstract: The method can include: determining image data; identifying a container using an object detector; and classifying a container state. The method can optionally include performing an action based on the container state classification. However, the method can additionally or alternatively include any other suitable elements. The method functions to detect and classify the state of bowls (i.e., complete/incomplete) to facilitate ingredient insertion into (unserved, ‘incomplete’) bowls along an assembly line.