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: 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: 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: A robot configured to be operable within a multi-robot system. The robot includes an input configured to receive global coordinate state information of the robot and of any neighboring robots or obstacles; and processing circuitry configured to: transform the global coordinate state information into a relative coordinate system that is with respect to the robot and is based on a type of desired formation of the robot and any neighboring robots or obstacles around a point; generate a reference formation algorithm which is based on the desired formation; and controlling, based on the reference formation algorithm and tracking errors between the desired formation and a current state of the robot, a trajectory of the robot to converge towards the desired formation while avoiding collisions with any neighboring robots or obstacles.

Abstract: Techniques are disclosed for a decentralized path and motion planning of autonomous agents within an environment. The planning may include determining if an active neighboring autonomous agent is present and selectively controlling the autonomous agent to operation in in an independent path planning operation mode and in a coordinating path planning operation mode, based on the detection of the neighboring agent(s).

Abstract: A human-robot collaboration system, including at least one processor; and a non-transitory computer-readable storage medium including instructions that, when executed by the at least one processor, cause the at least one processor to: predict a human atomic action based on a probability density function of possible human atomic actions for performing a predefined task; and plan a motion of the robot based on the predicted human atomic action.

Abstract: An apparatus of an autonomous device comprises one or more state estimators to estimate one or more states of the autonomous device, wherein the one or more state estimators are to generate one or more derivatives of translational measurements, orientation measurements, reference translational values, and reference orientation values, and one or more controllers to receive an output from the one or more state estimators to provide control signals to control the autonomous device. The one or more state estimators include a hardware differentiator to generate the one or more derivatives.

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: 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: 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: 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: 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: 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: 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: An apparatus of an autonomous device comprises one or more state estimators to estimate one or more states of the autonomous device, wherein the one or more state estimators are to generate one or more derivatives of translational measurements, orientation measurements, reference translational values, and reference orientation values, and one or more controllers to receive an output from the one or more state estimators to provide control signals to control the autonomous device. The one or more state estimators include a hardware differentiator to generate the one or more derivatives.

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.