Abstract: Described in detail herein is an automated fulfillment system including a computing system programmed to receive requests from disparate sources for physical objects disposed at one or more locations in a facility. The computing system can combine the requests, and group the physical objects in the requests based on object types or expected object locations. Autonomous robot devices can receive instructions from the computing system to retrieve a group of the physical objects and deposit the physical objects in storage containers.

Abstract: Described in detail herein is an automated fulfilment system including a computing system programmed to receive requests from disparate sources for physical objects disposed at one or more locations in a facility. The computing system can combine the requests, and group the physical objects in the requests based on object types or expected object locations. Autonomous robot devices can receive instructions from the computing system to retrieve a group of the physical objects and deposit the physical objects in storage containers.

Abstract: Described in detail herein is an automated fulfilment system including a computing system programmed to receive requests from disparate sources for physical objects disposed at one or more locations in a facility. The computing system can combine the requests, and group the physical objects in the requests based on object types or expected object locations. Autonomous robot devices can receive instructions from the computing system to retrieve a group of the physical objects and deposit the physical objects in storage containers.

Abstract: An autonomous vehicle system includes a body and a plurality of sensors coupled to the body and configured to generate a plurality of sensor measurements corresponding to the plurality of sensors. The system also includes a control unit configured to: receive inputs from a plurality of sources wherein the plurality sources comprise the plurality of sensors, the inputs comprise the plurality of sensor measurements; determine a confidence level of each input based on other inputs; prioritize, based on the confidence level associated with each input, the inputs; generate, based on the prioritization of the inputs and the confidence level, a combined input with a combined confidence level; and determine, based on the combined input and the combined confidence level, a mission task to be performed.

Abstract: Methodologies, systems, and computer-readable media are provided for generating a dynamic 3D communication map. Data is collected from a number of autonomous drones as they navigate through a particular area. The autonomous drones can collect environmental data, location data, signal strength data, signal usability data, etc. and transmit that data back to a computing system. The computing system analyzes the data received from the autonomous drones and generates a dynamic 3D communication map that indicates the signal strength and/or the signal usability of various wireless communication signals as a function of time and other variables.

Abstract: Described in detail herein is an automated fulfilment system including a computing system programmed to receive requests from disparate sources for physical objects disposed at one or more locations in a facility. The computing system can combine the requests, and group the physical objects in the requests based on object types or expected object locations. Autonomous robot devices can receive instructions from the computing system to retrieve a group of the physical objects and deposit the physical objects in storage containers.

Abstract: Described in detail herein is an automated fulfilment system including a computing system programmed to receive requests from disparate sources for physical objects disposed at one or more locations in a facility. The computing system can combine the requests, and group the physical objects in the requests based on object types or expected object locations. Autonomous robot devices can receive instructions from the computing system to retrieve a group of the physical objects and deposit the physical objects in storage containers.

Abstract: A technique for monitoring the quality of objects is disclosed. A container includes a multiple sensors and is configured to receive an object. The sensors monitor various metrics associated with the quality of the object, and a display is affixed to the container for displaying a visual indication of the quality of the object. The visual indication is based on data collected from the sensors. A quality monitoring module is executed by a processor to control the sensors to switch operation between a first mode of operation and a second mode of operation based on a detected change in one of the metrics monitored by the sensors.

Abstract: An automated tote routing systems that includes a conveyer belt, an array of sensors underneath the conveyer belt, and an identifier reader disposed with respect to the conveyer belt is discussed. The conveyer belt can be configured to receive a tote filled with physical objects. The array of sensors can detect a first set of attributes associated with the physical objects within the tote. The identifier reader can read and decode an identifier from a machine-readable element disposed on the tote. The array of sensors and identifier reader can transmit the first set of attributes and the identifier to a computing system. Based on the set of information associated with the physical objects and the set of attributes associated with the physical objects, a routing module executed by the computing system can automatically trigger the conveyer belt to route the tote to a selected distribution end of the conveyor belt.

Abstract: Described in detail herein is an temperature-controlled UAV delivery system. One or more physical objects can be stored inside a temperature-controlled storage unit of a UAV. A temperature controlling device can control the temperature of the interior volume of the temperature-controlled storage unit. Sensors can detect a temperature of the interior volume of the temperature-controlled storage unit. The computing system can control the temperature controlling device to adjust the temperature of the interior volume of the temperature-controlled storage unit to an ideal temperature for storing the one or more physical objects based on the attributes associated with the one or more physical objects.

Abstract: Described in detail herein is an automated fulfillment system including a computing system programmed to receive requests from disparate sources for physical objects disposed at one or more locations in a facility. The computing system can combine the requests, and group the physical objects in the requests based on object types or expected object locations. Autonomous robot devices can receive instructions from the computing system to retrieve a group of the physical objects and deposit the physical objects in storage containers.

Abstract: Described in detail herein is an autonomous fulfillment system using RFID devices. One or more RFID readers can be disposed throughout a facility can detect RFID tags disposed on or about physical objects picked up by the autonomous robotic devices. The computing system can determine whether there is an error in the physical objects picked up by the autonomous robotic device based on the identifiers. The computing system can instruct the autonomous robotic device to resolve the error. RFID readers can be disposed with respect to storage containers can detect the RFID tags disposed on or about the storage containers and the RFID tags disposed on the physical objects deposited in the storage containers. The computing system determine whether there is an error with the physical objects deposited in the storage containers. The computing system can instruct the autonomous robotic devices to resolve the error.

Abstract: A monitoring system for items in a delivery vehicle is described. Sensors disposed in the delivery vehicle are configured to sense data indicative of a current quality of items stored in the delivery vehicle. A computing device calculates navigation routes for the items in the vehicle and selects among the delivery routes at least partly based on sensor data relating to the monitored quality of the items.

Abstract: A virtual training system includes a 3D scanner in recording space and a camera. A scan of the recording space are received and combined to make a sequence of models of the recording space while a tasks is being performed. The model states are presented in sequence to a trainee in a playback space and the actions of the trainee are detected. Deviation of the trainee or objects in the playback space from the trainer and objects in the recording space may be detected and alerts generated. Scanning of the recording space may be accelerated by making a full scan followed by partial scans. The partial scans may be performed in response to detected movement.

Abstract: Systems and methods for managing communication of a plurality of unmanned aerial vehicles. The present invention can include a central server and a plurality of unmanned aerial vehicles including a master and secondary unmanned aerial vehicle. The master and secondary unmanned aerial vehicles can communicate with the central server and each other. The master and secondary unmanned aerial vehicle can deliver packages to different locations. In doing so, the master and secondary unmanned aerial vehicle can form a swarm that at least partially share a route for delivery of the packages to their destinations. The master unmanned aerial vehicle can be configured to: (i) receive delivery information for the master and secondary unmanned aerial vehicles, (ii) monitor communication between the swarm, and (iii) determine if the swarms encounters a risk.

Abstract: Systems, methods, and computer-readable storage media for identifying, on an autonomous vehicle which is traveling, a loss of a primary location system, and activating a secondary location system. The secondary location system performs a radio frequency sweep of a geographic area around the autonomous vehicle to identify radio frequency beacons, compares the radio frequency beacons to known ground stations, performs a visual scan of the geographic area to identify visual beacons, each visual beacon having a particular visual frequency, and compares the particular visual frequency of each of the visual beacons to known visual beacons. The secondary location system then identifies a current location of the autonomous vehicle by triangulating the verified radio frequency beacons and the verified visual beacons and the autonomous vehicle generates a route to a stopping location based on the current location produced by the secondary location system.

Abstract: Described in detail herein is an autonomous fulfillment system. The system includes the first computing system with an interactive display. The first computing system can transmit a request for physical objects from a facility. A second computing system can transmit instructions to autonomous robot devices to retrieve the physical objects from the facility. The second computing system can control the image capturing device of an autonomous robot device to capture a live image feed of at least one physical object picked up by the autonomous robot device. The second computing system can switch an input feed of the first computing system to display the live image feed on the interactive display of the first computing system. The second computing system can instruct the autonomous robot device to discard the physical objects picked up by the autonomous robot device and to pick up a replacement physical object.

Abstract: Systems, methods, and computer-readable storage media for intrusion protection on autonomous vehicles. As threats are detected, the nature of the threat is analyzed. A tiered response to the threat is then implemented, with an ultimate implementation including putting the autonomous vehicle in a “turtle” mode, and intermediate implementations including isolation of various subsystems. As the threats are identified and the autonomous vehicle implements the tiered responses, the autonomous vehicle records data regarding the efficiency the responses in diminishing the threat, then modifies the code which forms the autonomous algorithms such that, over time, the autonomous vehicle improves how it recognizes and responds to threats.

Abstract: Systems, methods, and computer-readable storage media for providing increased security to sensitive data acquired by autonomous vehicles. This is done using a flexible classification and storage system, where information about the autonomous vehicle's mission is used in conjunction with sensor data to determine if the sensor data is necessary to the mission. When the sensor data, the location of the autonomous vehicle, and other data indicate that the autonomous vehicle has captured non-mission specific data, it can be deleted, encrypted, fragmented, or otherwise partitioned, with the goal of protecting that sensitive information.

Abstract: Described in detail herein is an autonomous fulfillment system. The system includes the first computing system, with an interactive display. The first computing system can transmit a request for physical objects from a facility. A second computing system can transmit instructions autonomous robot devices to retrieve the physical objects from the facility. The second computing system can control the image capturing device of the autonomous robot device to capture a live image feed of the at least one physical object picked up by the at least autonomous robot device. The second computing system can switch an input feed of the first computing system to display the live image feed on the display of the first computing system. The second computing system, instruct the autonomous device to discard the physical objects picked up by the at least one autonomous robot device and to pick up a replacement physical object.