Abstract: Systems and methods may include a lift drone and a carrier drone to convey a payload. The lift drone may vertically lift the payload, alone or with the carrier drone, to a transfer location. The carrier drone may receive control of the payload at the transfer location, such as by receiving physical transfer of the payload, taking over conveyance of the payload from the lift drone, or the like. The lift drone may remain coupled with the payload or the carrier drone or may decouple after transfer.

Abstract: Systems and methods include receiving, values of one or more first external time variables from a first external node and values of one or more second external time variables from a second external node. The values of one or more local time variables of the local node are adjusted based at least upon the values of the one or more first external time variables and the values of the one or more second external time variables.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed herein including a monitoring system for a building including an in-wall guide for a drone, the in-wall guide extending behind at least one wall from a first location to a second location and a power delivery circuit in, or adjacent, the in-wall guide.

Abstract: An example unmanned aerial vehicle traffic signal and related methods are disclosed. The example unmanned aerial vehicle includes a housing, a rotor, a motor, a sensor, a traffic signal, and a processor. The rotor is to lift the housing off ground. The motor is to drive the rotor. The sensor is to monitor traffic. The traffic signal is carried by the housing. The processor is to control the traffic signal based on the traffic monitored by the sensor.

Abstract: Methods and apparatus for drone collision avoidance. Processing circuitry of a drone extracts information from an encoded image captured by a detection device with a field view overlapping the encoded image. Based on the extracted information a determination is made whether a collision will occur on the flight trajectory of the drone with an external source. The flight trajectory of the drone is then altered to avoid a collision.

Abstract: A method for calculating a time to contact of an autonomous vehicle, the method comprising: obtaining a plurality of event data an image, wherein the event data is associated with a pixel associated with a change in light intensity; determining a reference signal frequency associated with a transmitted light; identifying a select event data from the plurality of event data, wherein the light frequency associated with the select event data is substantially the same as the reference signal frequency; determining an object based on the select event data, wherein the object is fully enclosed by a bounding box comprising coordinates of a rectangular border; calculating a distance between a set of coordinates of the bounding box closest to the autonomous vehicle and the autonomous vehicle; and calculating the time to contact between the set of coordinates of the bounding box and the autonomous vehicle.

Abstract: Techniques are disclosed to facilitate, in autonomous vehicles, the robust detection and classification of objects in a scene using a static sensors in conjunction with event-based sensors. A trained system architecture may be implemented, and the fusion of both sensors thus allows for the consideration of scenes with overexposure, scenes with underexposure, as well as scenes in which there is no movement. In doing so, the autonomous vehicle may detect and classify objects in conditions in which each sensor, if operating separately, would not otherwise be able to classify (or classify with high uncertainty) due to the sensing environment.

Abstract: Transformable unmanned vehicles and related methods are disclosed. An example vehicle includes a body having, a first cap, a second cap spaced from the first cap, and a plurality of segments radially spaced relative to a longitudinal axis of the body. The segments are movable relative to the first cap and the second cap. The vehicle includes a payload supported by the first cap. An actuation system moves the segments relative to the first cap and the second cap to transform the body between a first configuration and a second configuration different than the first configuration.

Abstract: Methods, systems, and apparatus for audio noise reduction from a drone are disclosed. An example apparatus includes an acoustic sensor to gather acoustic data and at least one rotational motion sensor to gather rotational motion data of a first rotor and second rotational motion data of a second rotor. The example apparatus also includes an analyzer to identify a first filter that matches the first rotational motion data and identify a second filter that matches the second rotational motion data. The analyzer also is to filter the acoustic data into filtered acoustic data with the first identified filter and the second identified filter and generate an audio signal based on the filtered acoustic data.

Abstract: Methods and apparatus are described for drone collision avoidance that includes extracting first feature information from an image. The image is captured from a first camera oriented in a direction. Second feature information is received from an external source. The second feature information is extracted from a second image of the environment captured by a second camera oriented in the direction. The first feature information and the second feature information are matched. A second local frame of reference of the second feature information is transformed to a first local frame of reference of the first feature information to determine a location of the external source. If a collision with the external source will occur is determined based on the location of the external source and a current flight trajectory.

Abstract: Hybrid unmanned vehicles are disclosed. An example vehicle includes a housing and a rollerball rotatably coupled to the housing and a propulsion system supported by the housing. The propulsion system is to generate lift to enable the vehicle to navigate in a first mode of operation. The vehicle includes a rollerball rotatably coupled to the housing. The rollerball to enable the housing to navigate in a second mode of operation different than the first mode of operation. The propulsion system is to generate a drive force to enable the vehicle to navigate in the second mode of operation via the rollerball.

Abstract: Techniques are disclosed to facilitate cooperative mapping for safe and efficient trajectory planning and collision avoidance by allowing nearby agents to share contextual information. The described techniques also function to extend the mapping range of a single agent by leveraging observations made by multiple agents. Furthermore, the techniques as described herein function to reduce uncertainty in trajectory planning by allowing agents to “see” behind occlusions, thus taking advantage of observations made by neighboring agents from different points of view. An efficient hardware implementation of the system is also presented that leverages the methodologies as discussed herein.

Abstract: Systems and techniques for an architecture for contextual memories in map representation for 3D reconstruction and navigation are described herein. In an example, a system for contextual memory mapping is adapted to receive a data set of physical world sensor readings. The system may be further adapted to generate voxel data from the data set, the voxel data includes voxel coordinates and a physical world occupancy indicator. The system may be further adapted to select a block of addresses in the memory to store the voxel data. The system may be further adapted to generate a hash map to map voxel coordinates to memory locations in the block of addresses, the voxel coordinates having a contextual relationship that is maintained by the hash map. The system may be further adapted to store the voxel data at memory addresses based on the hash map.

Abstract: Unmanned aerial vehicles include a processor to determine whether a first location of an unmanned vehicle and a second location of a virtual event is within a threshold distance; and a game experience controller to: control the unmanned vehicle based on a first command associated with a non-augmented state of the unmanned vehicle in response to the first location of the unmanned vehicle and the second location of the virtual event being outside of the threshold distance; and in response to the first location of the unmanned vehicle and the second location of the virtual event being within the threshold distance, control the unmanned vehicle based on a second command associated with an augmented state of the unmanned vehicle to simulate the unmanned vehicle being affected by the virtual event.

Abstract: In one embodiment, a distributed oscillator computes a first error value based on a first state value for the distributed oscillator and first state values for other distributed oscillators, and computes a second error value based on a second state value for the distributed oscillator and second state values for the other distributed oscillators. The distributed oscillator computes a new first state value for the distributed oscillator based on the first error value, the first state value for the distributed oscillator, and the second state value for the distributed oscillator, and computes a new second state value for the distributed oscillator based on the second error value, the first state value for the distributed oscillator, and the second state value for the distributed oscillator. The distributed oscillator transmits the new first state value and the new second state value to the other distributed oscillators.

Abstract: Methods and apparatus for reducing energy consumed by drones during flight are disclosed. A drone includes a housing, a motor, receiver circuitry carried by the housing, and a route manager. The receiver circuitry is to receive airborne drone-generated wind data from an airborne drone located in an area within which a segment of a flight of the drone is to occur. The airborne drone-generated wind data is to be determined by an inertial measurement unit of the airborne drone. The route manager is to generate a route for the flight of the drone based on wind data, the wind data including the airborne drone-generated wind data. The route is to be followed by the drone during the flight. The route manager is to select at least one portion of the route to cause the drone to be at least partially propelled by wind to reduce energy consumed by the drone during the flight.

Abstract: In an embodiment, an apparatus includes a first logic to receive from a first node a synchronization portion of a message and to generate a set of state information using the synchronization portion, to synchronize the apparatus with the first node. The apparatus may further include a second logic to decrypt a data portion of the message using the set of state information to obtain a decrypted message. Other embodiments are described and claimed.

Abstract: Methods and apparatus for reducing energy consumed by drones during flight are disclosed. A drone includes a housing, a motor, and a route manager to generate a route for a flight of the drone based on wind data. The wind data includes turbine-generated wind data provided by turbines that detect airflows received at the turbines. The turbines are located in an area within which a segment of the flight of the drone is to occur. The route is to be followed by the drone during the flight to reduce energy consumed by the drone during the flight.

Abstract: Methods and apparatus to implement nonlinear control of vehicles moved using multiple motors, apparatus, systems and articles of manufacture are disclosed. An example apparatus includes a logic circuit configured to calculate virtual position control variables for a vehicle moved using multiple motors. The virtual position control variables calculated based on an application of a control law to position information of the vehicle. The control law is derived from a nonlinear model of movement of the vehicle. The logic circuit is configured further to calculate control inputs based on the virtual position control variables. The control inputs are to control the motors to navigate the vehicle along a designated path of movement.

Abstract: Methods, systems, and apparatus for audio noise reduction from a drone are disclosed. An example apparatus includes an acoustic sensor to gather acoustic data and at least one rotational motion sensor to gather rotational motion data of a first rotor and second rotational motion data of a second rotor. The example apparatus also includes an analyzer to identify a first filter that matches the first rotational motion data and identify a second filter that matches the second rotational motion data. The analyzer also is to filter the acoustic data into filtered acoustic data with the first identified filter and the second identified filter and generate an audio signal based on the filtered acoustic data.