Abstract: The present disclosure is directed to multi-use mobile robots that cater to both goods delivery and people mobility. These robots allow for seamless and dynamic transition between a rideable personal transport vehicle that may be driven by a user sitting in a removable robot seat, driven by the user standing onboard the vehicle, or driven by a second individual walking behind the multi-use robot. The multi-use robot may also function as an autonomous delivery vehicle, and can provide an option to allow both people and goods to be transported simultaneously. The multi-use robots can also integrate with mobile warehouses and neighborhood storage lockers and mobile warehouses, and provide last-mile handling of goods and supplies.

Abstract: Methods and apparatus for monitoring gas sensor sensitivity. The method includes repeatedly determining the response of a gas sensor by exposing the gas sensor to a gas and measuring the gas sensor response; and transmitting the response, information identifying the gas detector, and the time of the calibration to a remote computer. The remote computer then calculates a trend of sensitivity for the gas detector over time based on the received responses and corresponding time values and determines a renewal time when the calculated trend intersects a predetermined value.

Abstract: A method for controlling a robotic vehicle in a delivery environment includes causing the robotic vehicle to deploy from an autonomous vehicle (AV) at a first AV position in the delivery environment. The method further includes localizing, via a robotic vehicle controller, an initial position within a global reference map using a robot vehicle perception system, receiving, from the AV, a 3-dimensional (3D) augmented map and localizing an updated position in the delivery environment based on the 3D augmented map and the global reference map. The robot vehicle perception system senses obstacle characteristics, and generates a unified 3D augmented map with robot-sensed obstacle characteristics. The method further includes generating a dynamic path plan to a package delivery destination using the unified 3D augmented map, and actuating the robot vehicle to the package delivery destination according to the dynamic path plan.

Abstract: A fish tape tool includes a housing, a chamber defined in the housing, and a motor supported by the housing. The motor is configured to rotate in a first direction and a second direction that is opposite the first direction. An output reel is disposed in the chamber and is rotatable in response to receiving torque from the motor. A drum contains a fish tape and including a rotatable drum portion having an inner wall that is engaged by the output reel when the drum is inserted into the chamber of the housing. When the drum portion is rotated by the output reel in the first direction, fish tape is dispensed from the drum. When the drum portion is rotated by the output reel in the second direction, fish tape is retracted into the drum.

Abstract: A vacuum pump, which is connectable to an external system and configured to evacuate material from the external system, includes a main housing defining a motor housing, a pump housing, and a partition wall that separates the motor housing and the pump housing. The pump housing is sealed relative to the motor housing to form a compression chamber that holds a lubrication fluid. The vacuum pump further includes a motor assembly that is positioned within the motor housing and a pump assembly that is positioned within the compression chamber. The pump assembly is driven by the motor assembly and is in fluid communication with the compression chamber. The pump assembly includes a pump chamber, a rotor having vanes that is driven within the pump chamber, and a seal that is in sliding contact with the rotor. The seal is moveable relative to the rotor.

Abstract: A liveliness prediction output is provided from a liveliness biometric analysis task that is determined by a deep neural network based on an image provided from an image sensor wherein the liveliness biometric analysis task is performed in a deep neural network that includes a common feature extraction neural network and a plurality of task-specific neural networks including a face detection neural network, a body pose neural network and a liveliness neural network including a region of interest (ROI) detection neural network and a texture analysis neural network to determine the liveliness biometric analysis task by inputting the image to the common feature extraction neural network to determine latent variables. The latent variables can be input to the face detection neural network and the liveliness neural network. Output from the face detection neural network can be input to the ROI detection neural network.

Abstract: Apparatus and Methods for Aggregated Leak Detection. The method includes determining the location of multiple portable personal gas detectors as each gas detector is moved and monitoring the gas level associated with each determined location. This information is then collated by associating the transmitted location and associated gas levels. Zones of concern associated with elevated gas levels detected by multiple gas detectors are then identified.

Abstract: Systems and methods for fleet inspection and maintenance using a robot are provided. The robot may detect a maintenance issue of a vehicle of a fleet of vehicles via one or more sensors, generate a navigation route to a position proximal to the maintenance issue of the vehicle, traverse along the navigation route to the position, and execute a maintenance to rectify the maintenance issue of the vehicle. The robot may include a mobile base removably coupled to a modular platform for performing a maintenance task.

Abstract: This disclosure is generally directed to generating travel route information that is interpretable by a delivery robot for traversing a last mile of a delivery. In an example embodiment, an individual captures a video clip while moving along a travel route that is preferred by the individual for use by the delivery robot. The video clip is converted into a digital route map that the delivery robot uses to reach a package drop-off location on the property. In another example embodiment, an individual captures an image of a portion of the property and appends oral instructions to reach the package drop-off location. The image and the oral instructions are converted into a digital route map for use by the delivery robot. In yet another example embodiment, markers affixed to a surface of a traversable area on the property are used by the delivery robot to reach the package drop-off location.

Abstract: A wire stripper assembly includes a first bushing for stripping wire of a first size, a second bushing for stripping wire of a second size that is different than the first size, and a wire stripper having a housing and a drive mechanism. The first bushing has a first color. The second bushing has a second color that is different than the first color. The first bushing and the second bushing are alternately coupled to the housing for rotation about a longitudinal axis by the drive mechanism. Each of the first and second bushings has a tooth that is engageable with a wire for stripping an insulation jacket therefrom.

Abstract: A liveliness prediction output is provided from a liveliness biometric analysis task that is determined by a deep neural network based on an image provided from an image sensor wherein the liveliness biometric analysis task is performed in a deep neural network that includes a common feature extraction neural network and a plurality of task-specific neural networks including a face detection neural network, a body pose neural network and a liveliness neural network including a region of interest (ROI) detection neural network and a texture analysis neural network to determine the liveliness biometric analysis task by inputting the image to the common feature extraction neural network to determine latent variables. The latent variables can be input to the face detection neural network and the liveliness neural network. Output from the face detection neural network can be input to the ROI detection neural network.

Abstract: Output can be provided from a selected biometric analysis task that is one of a plurality of biometric analysis tasks based on an image provided from an image sensor. The selected biometric analysis task can be performed in a deep neural network that includes a common feature extraction neural network, a plurality of biometric task-specific neural networks and a plurality of expert pooling neural networks that perform the plurality of biometric analysis tasks by inputting the image to the common feature extraction network to determine latent variables. The latent variables can be input to the plurality of biometric task-specific neural networks to determine a plurality of first outputs. Concatenated first output results can be formed and the concatenated plurality of first result outputs and the latent variables can be input to the plurality of expert pooling neural networks to determine one or more biometric analysis task outputs.

Abstract: An expansion tool includes a housing, a motor supported by the housing and including a motor, a mandrel, and a drive mechanism configured to convert a rotational input from a motor shaft into translational movement of the mandrel. The expansion tool includes a first operating mode and a second operating mode. When the expansion tool is operated in the first operating mode, the drive mechanism is configured to reciprocate the mandrel between a retracted position and a first extended position. When the expansion tool is operated in the second operating mode, the drive mechanism is configured to reciprocate the mandrel between the retracted position and a second extended position different than the first extended position.

Abstract: Systems and methods for administering a hazard condition warning during a package delivery operation are provided. The system includes one or more sensors, e.g., radar sensors or cameras, configured to detect a hazard condition in a vicinity of a delivery vehicle and to generate data indicative of the hazard condition. The system further includes an operator sensor configured to detect a location of an operator relative to the delivery vehicle and one or more indicators, e.g., lights, a mobile application installed on a mobile phone, or an HMI of the vehicle, configured to generate an alert corresponding to the hazard condition. A processor of the system may determine whether the hazard condition is present based on the data indicative of the hazard condition, and cause, based on a presence of the hazard condition and the detected location of the operator, the one or more indicators to generate the alert.

Abstract: A strap hoist assembly comprises a strap hoist including a frame and a reel for reeling strap, and a drive assembly removably coupled to the strap hoist. The drive assembly includes a power unit and an onboard battery pack. The drive assembly is configured to provide an output torque to rotate the reel in a rotational direction to apply an output force to the strap. The strap hoist is configured to be powered by the drive assembly or manually operated when disconnected from the drive assembly.

Abstract: Embodiments include a server system including logic of an edge computing device. A network includes a cloud platform able to receive state change events from a state module, and execution of the program logic results in process steps of a method that include transmitting a plurality of attributes from the cloud platform to the at least one edge computing device, where the plurality of attributes can be associated with a device of a distributed environment coupled to the network. A further step includes receiving from the state module, by the edge computing device, current state data of the device, and a subsequent step includes performing a comparison based on a set of rules of the attributes, by the edge computing device, of the current state data. Further, based on the comparison, the method includes sending, by the edge computing device, an update to a human-machine-interface module.

Abstract: A wire stripper includes a housing and a bushing coupled to the housing and having a tooth engageable with a wire for stripping an insulation jacket therefrom. The wire stripper also includes a drive mechanism configured to rotate the bushing about a longitudinal axis. The wire stripper also includes a depth adjustment mechanism arranged in the housing along the longitudinal axis. The depth adjustment mechanism includes a depth stop member and a telescoping shaft to which the depth stop member is coupled. The telescoping shaft is configured to telescope within the housing as the depth stop member moves between a first position, in which a first distance is defined between the depth stop member and the tooth, and a second position, in which a second distance is defined between the depth stop member and the tooth. The first distance is greater than the second distance.

Abstract: A drain cleaner includes a shroud with a closed end and an open end opposite the closed end and a drum assembly positioned within the shroud. The drum assembly is rotatable relative to the shroud. The drum assembly includes an inner drum and a drum cover extending entirely over an open forward end of the inner drum. The drain cleaner also includes a flexible cable stored within a cavity defined by the inner drum and the drum cover of the drum assembly. The flexible cable is supported by the inner drum. The drain cleaner further includes a handle assembly coupled to and extending rearwardly from the shroud. The handle assembly includes a motor, a grip, and an actuator to selectively energize the motor. The actuator is positioned in an area defined between the grip and the shroud.

Abstract: A method includes obtaining state information from one or more sensors of a digital twin. The method includes determining an action at the first routing control location based on the state information, where the action includes one of a pallet merging operation and a pallet splitting operation, and determining a consequence state based on the action. The method includes calculating a transient production value based on the consequence state and a transient objective function, calculating a steady state production value based on the consequence state and a steady state objective function, and selectively adjusting one or more reinforcement parameters of the reinforcement learning system based on the transient production value and the steady state production value.

Abstract: A first computer and a second computer are each connected to a communication network. User data is generated for a user by the first computer based on receiving, from the second computer, initial enrollment biometric data for the user. The user is authorized by the first computer based on a confidence score for challenge biometric data exceeding a first confidence threshold. Then the user data is updated with updated enrollment biometric data by the first computer based on a confidence score for the updated enrollment biometric data exceeding a second confidence threshold. The second confidence threshold is greater than the first confidence threshold. The initial enrollment biometric data is deleted by the second computer after a predetermined time of receiving the initial enrollment biometric data.