Embodiments of the invention include a drone system or method for distracting a threat with a light source. In some embodiments, an environment can be scanned with a sensor that produces sensor data. A threat within the environment can be identified from the sensor data, and the location of the threat can be determined. The light source can be aimed toward the threat; and light may be directed from the light source toward the threat.

When a non-operable notification is output from any of a plurality of operating vehicles, an operation schedule creator creates a substitute vehicle introduction operation schedule based on planned stopping times and a target velocity determined by a normal operation schedule, as an operation schedule to be provided, to each of operating vehicles other than a non-operable vehicle which has output the non-operable notification, when the operating vehicle passes an operation schedule updating location for a first time after the non-operable notification is output.

When a non-operable notification is output from any of a plurality of operating vehicles, an operation schedule creator creates a substitute vehicle introduction operation schedule based on planned stopping times and a target velocity determined by a normal operation schedule, as an operation schedule to be provided, to each of operating vehicles other than a non-operable vehicle which has output the non-operable notification, when the operating vehicle passes an operation schedule updating location for a first time after the non-operable notification is output.

Spatiotemporal robotic navigation may include providing a set of robots non-conflicting access to the same shared resources at different times so that the robots may operate without continually accounting for the locations of the other robots and workers operating in the particular site, without continually planning or updating paths after determining an initial path, and without continuously adjusting movements as the robots near one another. The spatiotemporal robotic navigation involves generating spatiotemporal plans. Each plan has a set of objectives that a robot is to execute by different time intervals. Each plan is generated so as to not conflict with the resources being accessed by other robots at time intervals set in the plans of other robots.

In some embodiments, a computer-implemented method of managing a fleet of unmanned aerial vehicles (UAVs) is provided. A fleet management computing system receives telemetry information from a plurality of UAVs. The fleet management computing system generates a map interface having a plurality of UAV icons based on the telemetry information. The fleet management computing system receives a selection of an initial group of UAV icons via the map interface, wherein the initial group of UAV icons includes two or more UAV icons. The fleet management computing system receives a de-selection of one or more UAV icons from the initial group of UAV icons to create a final selected group of UAV icons. The fleet management computing system transmits a command to UAVs associated with the UAV icons of the final selected group of UAV icons.

A technique for operating unmanned aerial vehicles (UAVs) in a terminal area from which the UAVs are staged includes charging a plurality of the UAVs on charging pads disposed in a staging array at the terminal area. Merchant facilities for preparing packages for delivery by the UAVs are disposed about a periphery of the staging array. The UAVs are relocated under their own propulsion from interior charging pads to peripheral loading pads of the staging array as the peripheral loading pads become available and the UAVs are deemed sufficiently charged and ready for delivery missions.

Systems and methods provide for enabling an autonomous vehicle to provide road assistance to a vehicle. The autonomous vehicle can analyze sensor data about the vehicle captured by one or more of its sensors as it navigates a route. Based on the analysis of the sensor data, the autonomous vehicle can determine that the vehicle needs maintenance. The autonomous vehicle can proactively send a request, based on the determination, to initiate a towing mechanism to tow the vehicle. Based on receiving an acceptance of the request from the vehicle, the autonomous vehicle can activate the towing mechanism.

Methods and enhanced apparatus used in such methods are described that a dispatched logistics operation for a deliverable item from a hold-at-location (HAL) logistics facility having a secured storage and using a modular autonomous bot apparatus assembly and a dispatch server. The bot apparatus assembly picks up and delivers the item from the HAL facility in response to a delivery dispatch command from the dispatch server. In response, the MAM of the bot verifies compatibility of modular components for the operation, controls receiving of the deliverable item from the secured storage at the HAL facility, then autonomously causes movement to the delivery destination. The MAM notifies the customer before delivery of the approaching delivery, authenticates delivery is to the authorized customer, provides access to the item within the bot apparatus assembly, monitors unloading of the item, then autonomously moves back to the HAL facility.

Systems and methods are provided for temperature regulation in an autonomous vehicle. In particular, systems and methods are provided for regulating the interior temperature of a delivery container in an autonomous vehicle. In various implementations, the delivery container includes one or more compartments, and a thermal management system is provided for regulating the temperature of each of the compartments.

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Such assessment may be performed to determine the robustness of autonomous systems, including the use of virtual assessment of software components within a simulated environment. To this end, a server may retrieve one or more routines associated with autonomous operation. The server may also generate a set of test data associated with test conditions. The server may also execute an emulator that virtually simulates autonomous environment. The test data may be presented to the routines executing in the emulator to generate output data. The server may then analyze the output data to determine a quality metric.