Abstract: Disclosed herein are systems, devices, and methods for real-time motion and path planning. The real-time motion and path planner may generate occupancy information about an environment around a robot. The occupancy information represents defined volumes of space of the environment, and each defined volume of space is associated with a corresponding occupancy probability. The motion/path planner also determines a sequence of robot configurations between a starting and a target configuration based on the occupancy information, wherein the sequence of robot configurations defines poses of the robot that occupy selected ones of the defined volumes of space. The motion/path planner also generates an instruction for the robot based on the sequence of robot configurations, wherein the instruction includes trajectory information to control the robot to move from the starting configuration to the target configuration through the sequence of robot configurations.

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: Systems, apparatus, articles of manufacture, and methods are disclosed to calibrate imaging devices. An example apparatus includes interface circuitry, machine readable instructions, and programmable circuitry to at least one of instantiate or execute the machine readable instructions to segregate an image into regions. The example apparatus binarizes the image by associating a first one of the regions with a surface, and associating a second one of the regions with background objects. The example apparatus also generates a quadric corresponding to the surface, distinguishes a first quantity of pixels from a second quantity of pixels from the binarized image, the first quantity of pixels associated with the first one of the regions and the second quantity of pixels associated with the second one of the regions, adjusts parameters of the quadric based on the first quantity of the pixels, and calculates calibration parameters based on the adjusted parameters of the quadric.

Abstract: Disclosed herein are systems, devices, and methods for real-time determinations of likelihoods for possible trajectories of a collaborator in a workspace with a robot. The system determines a current kinematic state of the collaborator and determines a goal of the collaborator based on occupancy information about objects in the workspace. The system also determines a possible trajectory for the collaborator based on the goal and the current kinematic state and determines a short-horizon trajectory for the collaborator based on previously observed kinematic states of the collaborator towards the goal. The system also determines a likelihood that the collaborator will follow the possible trajectory based on the short-horizon trajectory, the goal, and the current kinematic state. The system also generates a movement instruction to control movement of the robot based on the likelihood that the collaborator will follow the possible trajectory.

Abstract: A localization system includes a first sensor, configured to detect a vibration and generate a first electrical signal in response to the detection of the vibration; a second sensor, configured to detect a vibration and generate a second electrical signal in response to the detection of the vibration; a third sensor, configured to detect a vibration and generate a third electrical signal in response to the detection of the vibration; and a processor, configured to determine a position of a source of the vibration based on the first electrical signal, the second electrical signal, and the third electrical signal.

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: 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: 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: Unmanned aerial vehicles and related methods and systems are disclosed. An example unmanned aerial vehicle, comprising: a body and a propulsion source to propel the unmanned aerial vehicle during flight; and a display carried by the unmanned aerial vehicle to display a message to coordinate traffic, the display actuatable between a deployed position to enable the message to be conveyed and a stowed position in which aerodynamics of the unmanned aerial vehicle are enhanced.

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 and apparatus for training a neural network are disclosed. An example apparatus includes a neural network trainer to determine an amount of training error experienced in a prior training epoch of a neural network, and determine a gradient descent value based on the amount of training error. A learning rate determiner is to calculate a learning rate based on the gradient descent value and a selected number of epochs such that a training process of the neural network is completed within the selected number of epochs, the neural network trainer to update weighting parameters of the neural network based on the learning rate.

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: Unmanned aerial vehicles and related methods and systems are disclosed. An example unmanned aerial vehicle, comprising: a body and a propulsion source to propel the unmanned aerial vehicle during flight; and a display carried by the unmanned aerial vehicle to display a message to coordinate traffic, the display actuatable between a deployed position to enable the message to be conveyed and a stowed position in which aerodynamics of the unmanned aerial vehicle are enhanced.