Abstract: Apparatus and methods related to generating roadmaps are provided. A layout of an environment can be displayed on a display. Input data indicative of a plurality of shapes placed on the layout can be received, where each shape corresponds to an aisle of a plurality of aisles. For each aisle, lanes can be generated based on a width of the aisle, and the lanes extend along the aisle such that a robotic device can traverse each lane. An intersection between a first shape and second shape can be identified, where the first and second shape correspond to a first and second aisle. Responsive to identifying the intersection and based on a swept space of the robotic device, a curve that connects a first lane of the first aisle to a second lane of the second aisle can be generated. Then, a roadmap that comprises the aisles and curve can be generated.

Abstract: An example method is carried out in a warehouse environment having a plurality of inventory items located therein, each having a corresponding on-item identifier. The method involves determining a target inventory item having a target on-item identifier. The method also involves determining that a first inventory item having a first on-item identifier is loaded onto a first robotic device. The method further involves transmitting a request to verify the first on-item identifier. The method still further involves receiving data captured by a sensor of the second robotic device. The method yet further involves (i) analyzing the received data to determine the first on-item identifier, (ii) comparing the first on-item identifier and the target on-item identifier, and (iii) responsive to comparing the first on-item identifier and the target on-item identifier, performing an action.

Abstract: The invention generally provides a sample preparation vessel including a flexible substrate defining at least one sealable opening adapted and configured to receive a solid sample; at least one fitting; and at least one filter adjacent to the at least one fitting, the filter adapted and configured to permit extracted fluids to exit the vessel while retaining solid particles, as well as vessels, circuits, systems, and related methods for sample preparation, extraction, and analysis.

Abstract: Examples described may enable consolidating pallets of items in a warehouse. An example method includes receiving real-time item information including pallet locations in a warehouse and inventory of items arranged on the pallets; based on the real-time item information, identifying a set of pallets of which at least one pallet includes less than a threshold quantity of a type of item; receiving real-time robotics information and determining, based on the real-time item and robotics information, an amount of time to condense the items on the set of pallets into a single pallet and a quantity of pallets that will become empty as a result of condensing the items; and, based on the amount of time being less than a threshold time and the quantity of pallets exceeding a threshold quantity of pallets, causing robotic devices to condense the items into the single pallet.

Abstract: The present invention features compositions and methods for quantifying detection of a target oligonucleotide in a sample in real time. These methods are compatible with target oligonucleotides amplified using a NEAR reaction.

Abstract: An example system includes a robotic device deployed in a warehouse environment including a plurality of inventory items. The system also includes a camera coupled to the robotic device, configured to capture image data. The system also includes a computing system configured to receive the captured image data. The computing system is configured to, based on the received image data, generate a navigation instruction for navigation of the robotic device. The computing system is also configured to analyze the received image data to detect one or more on-item visual identifiers corresponding to one or more inventory items. The computing system is further configured to, for each detected visual identifier, (i) determine a warehouse location of the corresponding inventory item, (ii) compare the determined warehouse location to an expected location, and (iii) initiate an action based on the comparison.

Abstract: Examples described may enable consolidating pallets of items in a warehouse. An example method includes receiving real-time item information including pallet locations in a warehouse and inventory of items arranged on the pallets; based on the real-time item information, identifying a set of pallets of which at least one pallet includes less than a threshold quantity of a type of item; receiving real-time robotics information and determining, based on the real-time item and robotics information, an amount of time to condense the items on the set of pallets into a single pallet and a quantity of pallets that will become empty as a result of condensing the items; and, based on the amount of time being less than a threshold time and the quantity of pallets exceeding a threshold quantity of pallets, causing robotic devices to condense the items into the single pallet.

Abstract: Examples described may enable rearrangement of pallets of items in a warehouse to an optimal layout. An example method includes receiving real-time item information including pallet locations in a warehouse and real-time inventory of items arranged on the pallets; determining a likelihood of demand for future access to the pallets based on a pallet relocation history and item receiving/shipment expectations; based on the real-time item information and the likelihood of demand, determining an optimal controlled-access dense grid layout in which distances of the pallets from a center of the layout are related to the likelihood of demand; receiving real-time robotics information and using the real-time robotics information to determine an amount of time to rearrange the pallets to the optimal layout; and, based on the amount of time to rearrange the pallets being less than a threshold, causing the robotic devices to rearrange the pallets to the optimal layout.

Abstract: Methods and systems for detecting sensor orientation characteristics using marker-based localization are disclosed herein. In one aspect, a robotic device can: receive a map of a horizontal marker plane that includes mapped positions of a first marker and a second marker arranged in the horizontal marker plane; receive, from a sensor configured to scan a two-dimensional sensor plane, sensor data indicative of positions of the first and second markers relative to the sensor; determine measured positions of the first and second markers based on the sensor data and a current position of the sensor; determine a difference vector between a first vector that connects the mapped positions of the first and second markers and a second vector that connects the measured positions of the first and second markers; and determine, based on the difference vector, an orientation of the two-dimensional sensor plane relative to the horizontal marker plane.

Abstract: Examples described may enable rearrangement of pallets of items in a warehouse to an optimal layout. An example method includes receiving real-time item information including pallet locations in a warehouse and real-time inventory of items arranged on the pallets; determining a likelihood of demand for future access to the pallets based on a pallet relocation history and item receiving/shipment expectations; based on the real-time item information and the likelihood of demand, determining an optimal controlled-access dense grid layout in which distances of the pallets from a center of the layout are related to the likelihood of demand; receiving real-time robotics information and using the real-time robotics information to determine an amount of time to rearrange the pallets to the optimal layout; and, based on the amount of time to rearrange the pallets being less than a threshold, causing the robotic devices to rearrange the pallets to the optimal layout.

Abstract: Examples described may enable consolidating pallets of items in a warehouse. An example method includes receiving real-time item information including pallet locations in a warehouse and inventory of items arranged on the pallets; based on the real-time item information, identifying a set of pallets of which at least one pallet includes less than a threshold quantity of a type of item; receiving real-time robotics information and determining, based on the real-time item and robotics information, an amount of time to condense the items on the set of pallets into a single pallet and a quantity of pallets that will become empty as a result of condensing the items; and, based on the amount of time being less than a threshold time and the quantity of pallets exceeding a threshold quantity of pallets, causing robotic devices to condense the items into the single pallet.

Abstract: The present invention features compositions and methods for quantifying detection of a target oligonucleotide in a sample in real time. These methods are compatible with target oligonucleotides amplified using a NEAR reaction.

Abstract: An example method includes receiving image data captured by a sensor on a robotic device. The robotic device is in a warehouse, including multiple inventory items stored at storage locations in the warehouse. Each inventory item has an on-item identifier that identifies it in a warehouse management system (WMS), each storage location has a storage-location identifier that identifies it in the WMS, and a first on-item identifier for a first inventory item is associated in the WMS with a first storage-location identifier for a first storage location. The method includes analyzing the received sensor data to detect an identifier captured by the sensor. The detected identifier includes one or both of the first on-item identifier and the first storage-location identifier. The method includes determining a warehouse location associated with the detected identifier and, based on the warehouse location, determining a location of the robotic device within the warehouse.

Abstract: Example methods and systems enable rearrangement of a warehouse to an optimal layout determined according to customizable goals. An example method includes receiving, at a warehouse management system (WMS), information of a warehouse and items of the warehouse, identifying an item shipment expectation including new items expected to be received at the warehouse at a future date and items present at the warehouse marked for delivery at the future date, determining an optimal layout of the items of the warehouse at a present date based on the item shipment expectation, determining an amount of time to rearrange the items, by one or more of robotic devices rearranging the items, to the optimal layout based on a time measurement for robotic devices to perform tasks, and determining to rearrange the items of the warehouse based on the amount of time to rearrange the items being less than a threshold amount of time.

Abstract: Examples described may enable consolidating pallets of items in a warehouse. An example method includes receiving real-time item information including pallet locations in a warehouse and inventory of items arranged on the pallets; based on the real-time item information, identifying a set of pallets of which at least one pallet includes less than a threshold quantity of a type of item; receiving real-time robotics information and determining, based on the real-time item and robotics information, an amount of time to condense the items on the set of pallets into a single pallet and a quantity of pallets that will become empty as a result of condensing the items; and, based on the amount of time being less than a threshold time and the quantity of pallets exceeding a threshold quantity of pallets, causing robotic devices to condense the items into the single pallet.

Abstract: Examples described may enable rearrangement of pallets of items in a warehouse to an optimal layout. An example method includes receiving real-time item information including pallet locations in a warehouse and real-time inventory of items arranged on the pallets; determining a likelihood of demand for future access to the pallets based on a pallet relocation history and item receiving/shipment expectations; based on the real-time item information and the likelihood of demand, determining an optimal controlled-access dense grid layout in which distances of the pallets from a center of the layout are related to the likelihood of demand; receiving real-time robotics information and using the real-time robotics information to determine an amount of time to rearrange the pallets to the optimal layout; and, based on the amount of time to rearrange the pallets being less than a threshold, causing the robotic devices to rearrange the pallets to the optimal layout.

Abstract: An example method is carried out in a warehouse environment having a plurality of inventory items located therein, each having a corresponding on-item identifier. The method involves determining a target inventory item having a target on-item identifier. The method also involves determining that a first inventory item having a first on-item identifier is loaded onto a first robotic device. The method further involves transmitting a request to verify the first on-item identifier. The method still further involves receiving data captured by a sensor of the second robotic device. The method yet further involves (i) analyzing the received data to determine the first on-item identifier, (ii) comparing the first on-item identifier and the target on-item identifier, and (iii) responsive to comparing the first on-item identifier and the target on-item identifier, performing an action.

Abstract: An example system includes a robotic device deployed in a warehouse environment including a plurality of inventory items. The system also includes a camera coupled to the robotic device, configured to capture image data. The system also includes a computing system configured to receive the captured image data. The computing system is configured to, based on the received image data, generate a navigation instruction for navigation of the robotic device. The computing system is also configured to analyze the received image data to detect one or more on-item visual identifiers corresponding to one or more inventory items. The computing system is further configured to, for each detected visual identifier, (i) determine a warehouse location of the corresponding inventory item, (ii) compare the determined warehouse location to an expected location, and (iii) initiate an action based on the comparison.

Abstract: An example method is carried out in a warehouse environment having a plurality of inventory items located therein, each having a corresponding on-item identifier. The method involves determining a target inventory item having a target on-item identifier. The method also involves determining that a first inventory item having a first on-item identifier is loaded onto a first robotic device. The method further involves transmitting a request to verify the first on-item identifier. The method still further involves receiving data captured by a sensor of the second robotic device. The method yet further involves (i) analyzing the received data to determine the first on-item identifier, (ii) comparing the first on-item identifier and the target on-item identifier, and (iii) responsive to comparing the first on-item identifier and the target on-item identifier, performing an action.

Abstract: The present invention provides methods for rapidly identifying an RNA viral infection using an isothermal nucleic acid amplification reaction that can be carried out extracted RNA in the context of a crude biological sample.