Abstract: Systems and methods for training an object detection network are described. Embodiments train an object detection network using a labeled training set, wherein each element of the labeled training set includes an image and ground truth labels for object instances in the image, predict annotation data for a candidate set of unlabeled data using the object detection network, select a sample image from the candidate set using a policy network, generate a labeled sample based on the selected sample image and the annotation data, wherein the labeled sample includes labels for a plurality of object instances in the sample image, and perform additional training on the object detection network based at least in part on the labeled sample.

Abstract: The system can include a set of joints, a controller, and a model engine; and can optionally include a support structure and an end effector. Joints can include: a motor, a transmission mechanism, an input sensor, and an output sensor. The system can enable articulation of the plurality of joints.

Abstract: Examples provide a system and method for optimizing single piece versus multi-piece shipment for source-carrier combinations. A manager component calculates an estimated shipping cost for all possible combinations of source-carrier associated with delivery of items from the source to a destination. The system iteratively calculates a cost for shipping the item with every combination of carriers and sources as a single piece only packaging, as well as a multi-piece packaging where applicable based on rate cards for the carriers. The combination of source-carrier and boxing method providing the lowest estimated shipping cost in a plurality of calculated shipping costs is selected for order fulfillment. The selected carrier is assigned to deliver the ordered items from the source location to the destination location. A notification can be sent to the user identifying the selected carrier and estimated date of delivery of the items.

Abstract: The system can include a set of joints, a controller, and a model engine; and can optionally include a support structure and an end effector. Joints can include: a motor, a transmission mechanism, an input sensor, and an output sensor. The system can enable articulation of the plurality of joints.

Abstract: The system can include a set of joints, a controller, and a model engine; and can optionally include a support structure and an end effector. Joints can include: a motor, a transmission mechanism, an input sensor, and an output sensor. The system can enable articulation of the plurality of joints.

Abstract: The system can include a set of joints, a controller, and a model engine; and can optionally include a support structure and an end effector. Joints can include: a motor, a transmission mechanism, an input sensor, and an output sensor. The system can enable articulation of the plurality of joints.