Abstract: A computer-implemented system and method relate to gesture recognition. A machine learning model includes a first subnetwork, a second subnetwork, and a third subnetwork. The first subnetwork generates feature data based on sensor data, which includes a gesture. The feature data is divided into a set of patches. The second subnetwork selects a target patch of feature data from among the set of patches. The third subnetwork generates gesture data based on the target patch of feature data. The gesture data identifies the gesture of the sensor data. Command data is generated based on the gesture data. A device is controlled based on the command data.

Abstract: A computer-implemented system and method relate to gesture recognition. A machine learning system is trained using a training dataset of sensor data that include a set of gestures. The training dataset includes at least a first subset that displays a first gesture. Loss data is generated based on a first loss function that includes a first cross entropy loss and a second cross entropy loss. Parameters of the machine learning system are updated based on the loss data. The machine learning system is outputted and configured for gesture recognition of the set of gestures. The machine learning system includes (i) a first subnetwork to generate feature data based on the sensor data, (ii) a second subnetwork to extract a selected patch of the feature data, and (iii) a third subnetwork to generate gesture data based on a classification of the corresponding feature data of the selected patch. The first cross entropy loss is based on a first performance of the second subnetwork in relation to the training dataset.

Abstract: A method is disclosed for improving a mobile robot that is configured to perform a task in an environment using an operating procedure. Data is received that was recorded by the mobile robot using one or more sensors as the mobile robot navigates the environment to perform the task. A database and/or a model associated with the environment is updated to incorporate the recorded data. The operating procedure of the mobile robot can be modified, based on the database and/or the model, to generate a modified operating procedure for performing the task in the environment that improves a performance of the mobile robot. Additionally, a recommendation for improving the performance of the mobile robot when performing the task in the environment can be determined, based on the database and/or the model, and displayed to a user for consideration.

Abstract: A system and method are disclosed herein for developing robust semantic mapping models for estimating semantic maps from LiDAR scans. In particular, the system and method enable the generation of realistic simulated LiDAR scans based on two-dimensional (2D) floorplans, for the purpose of providing a much larger set of training data that can be used to train robust semantic mapping models. These simulated LiDAR scans, as well as real LiDAR scans, are annotated using automated and manual processes with a rich set of semantic labels. Based on the annotated LiDAR scans, one or more semantic mapping models can be trained to estimate the semantic map for new LiDAR scans. The trained semantic mapping model can be deployed in robot vacuum cleaners, as well as similar devices that must interpret LiDAR scans of an environment to perform a task.

Abstract: An endoluminal device for repairing an aortic dissection and preventing future aortic dissections, the device including a plurality of struts with at least one of the plurality of struts having a mid-strut portion having two or more secondary struts, the device being configured to be secured within a false lumen of the aorta and contain filler material in order to encourage thrombosis within the false lumen.

Abstract: An endoluminal device for repairing an aortic dissection and preventing future aortic dissections, the device including a plurality of struts with at least one of the plurality of struts having a mid-strut portion having two or more secondary struts, the device being configured to be secured within a false lumen of the aorta and contain filler material in order to encourage thrombosis within the false lumen.