Abstract: An approach to place recognition from an image makes use of the detection of objects at a set of known places as well as at an unknown place. Images of the detected objects in an image of the unknown place are processed to yield respective numerical descriptors, and these descriptors are used to compare the unknown place to the known places to recognize the unknown place. At least some embodiments make use of a trained parameterized image processor to transform an image of an object to an object descriptor, and the training of the processor is meant to preserve distinctions between different instances of a type of object, as well as distinctions between entirely different types of objects.

Abstract: In some aspects, a system comprises a computer hardware processor and a non-transitory computer-readable storage medium storing processor-executable instructions for receiving, from one or more sensors, sensor data relating to a robot; generating, using a statistical model, based on the sensor data, first control information for the robot to accomplish a task; transmitting, to the robot, the first control information for execution of the task; and receiving, from the robot, a result of execution of the task.

Abstract: A controller for an autonomous vehicle is trained using simulated paths on a roadway and simulated observations that are formed by transforming images previously acquired on similar paths on that roadway. Essentially an unlimited number of paths may be simulated, enabling optimization approaches including reinforcement learning to be applied to optimize the controller.

Abstract: Systems and methods described herein relate to vehicular navigation and localization. One embodiment extracts perceptual features from sensor data; extracts unrouted-map features from unrouted map data; combines the perceptual features and the unrouted-map features to produce first combined features data; outputs, based at least in part on the first combined features data, parameters of a probability distribution for one or more steering trajectories that are available to a vehicle; and performs a localization of the vehicle based, at least in part, on the parameters of the probability distribution.

Abstract: Described is a method of forming a structure having viscoelastic properties. The method can include a) depositing a layer of droplets of a solidifying material and a non-solidifying material, the droplets being deposited according to an occupancy matrix specifying voxels for the solidifying and non-solidifying materials, the solidifying and non-solidifying material being interspersed within the occupancy matrix, the occupancy matrix being generated by a probabilistic function; b) exposing the droplets of solidifying material to ultraviolet radiation to cure the solidifying material; and c) repeating a) and b) to deposit additional layers of droplets of solidifying and non-solidifying materials, thereby forming the structure having viscoelastic properties.

Abstract: Understanding the intent of human drivers and adapting to their driving styles is used to increased efficiency and safety of autonomous vehicles (AVs) by enabling them to behave in safe and predictable ways without requiring explicit inter-vehicle communication. A Social Value Orientation (SVO), which quantifies the degree of an agent's selfishness or altruism, is estimated by the AV for other vehicles to better predict how they will interact and cooperate with others. Interactions between agents are modeled as a best response game wherein each agent negotiates to maximize their own utility. A dynamic game solution uses the Nash equilibrium, yielding an online method of predicting multi-agent interactions given their SVOs. This approach allows autonomous vehicles to observe human drivers, estimate their SVOs, and generate an autonomous control policy in real time.

Abstract: A method of non-line-of-sight (NLoS) obstacle detection for an ego vehicle is described. The method includes capturing a sequence of images over a period with an image capture device. The method also includes storing the sequence of images in a cyclic buffer. The method further includes registering each image in the cyclic buffer to a projected image. The method includes performing the registering by estimating a homography H for each frame of the sequence of images to project to a view point of a first frame in the sequence of images and remove motion of the ego vehicle in the projected image. The method also includes enhancing the projected image. The method further includes classifying the projected image based on a scene determination. The method also includes issuing a control signal to the vehicle upon classifying the projected image.

Abstract: An approach to place recognition from an image makes use of the detection of objects at a set of known places as well as at an unknown place. Images of the detected objects in an image of the unknown place are processed to yield respective numerical descriptors, and these descriptors are used to compare the unknown place to the known places to recognize the unknown place. At least some embodiments make use of a trained parameterized image processor to transform an image of an object to an object descriptor, and the training of the processor is meant to preserve distinctions between different instances of a type of object, as well as distinctions between entirely different types of objects.

Abstract: Systems and methods for predicting the trajectory of an object are disclosed herein. One embodiment receives sensor data that includes a location of the object in an environment of the object; accesses a location-specific latent map, the location-specific latent map having been learned together with a neural-network-based trajectory predictor during a training phase, wherein the neural-network-based trajectory predictor is deployed in a robot; inputs, to the neural-network-based trajectory predictor, the location of the object and the location-specific latent map, the location-specific latent map providing, to the neural-network-based trajectory predictor, a set of location-specific biases regarding the environment of the object; and outputs, from the neural-network-based trajectory predictor, a predicted trajectory of the object.

Abstract: An object detection method includes receiving sensor data including a number of images associated with a sensor region as the actor traverses an environment, the plurality of images characterizing changes of illumination in the sensor region over time, the sensor region including a region to be traversed by the actor in the future, processing the plurality of images determine a change of illumination in sensor the region over time. The processing includes registering the plurality of images to a common coordinate system based at least in part on odometry data characterizing the actor's traversal of the environment, determining the change of illumination in the sensor region over time based on the registered plurality of images. The method further includes determining an object detection result based at least in part on the change of illumination in the sensor region over time.

Abstract: A modular robotic system that includes a plurality of self-configuring robots. Each self-configuring robot includes a frame structure having a plurality of cylindrical bonding magnets positioned along the edges of the frame structure. The frame structure includes magnetic, non-gendered, hinges on any of the edges of the frame. The hinges provide enough force to maintain a pivot axis through various motions. The cylindrical bonding magnets are free to rotate allowing for multiple self-configurations with other like self-configuring robots. A movement generator is positioned within the frame structure that pivots to generate multi-axis movement allowing both robust self-reconfiguration with the other self-configuring robots and independent locomotion.

Abstract: A modular robotic system that includes a plurality of self-configuring robots. Each self-configuring robot includes a frame structure having a plurality of cylindrical bonding magnets positioned along the edges of the frame structure. The frame structure includes magnetic, non-gendered, hinges on any of the edges of the frame. The hinges provide enough force to maintain a pivot axis through various motions. The cylindrical bonding magnets are free to rotate allowing for multiple self-configurations with other like self-configuring robots. A movement generator is positioned within the frame structure that pivots to generate multi-axis movement allowing both robust self-reconfiguration with the other self-configuring robots and independent locomotion.

Abstract: Non-planar shearing auxetic structures, devices, and methods are provided herein. In some embodiments, a non-planar shearing auxetic structure can include a mathematically compact surface with an auxetic pattern of repeating unit cells. The shearing auxetic structure can have a contracted configuration and an expanded configuration, and, when in the compact configuration, can be configured to move to the expanded configuration while generating a net shear on the surface. Shearing auxetic structures can have handedness and, in some embodiments, multiple handed shearing auxetic structures can be joined to create rigid or semi-rigid composite structures, e.g., by arranging differently-handed structures concentrically wherein two or more structures lock against each other. Handed shearing auxetic structures can also provide actuators to convert rotation or other motion to translation, volume expansion, bending, twisting, etc. These structures have many applications, e.g.

Abstract: An approach to autonomous navigation of a vehicle augments a static map of an environment with a clutter map characterizing a risk of encountering an object that is not represented in the static map of the environment. For example, the clutter map may be based on locations and velocities of those objects, and route planning may avoid planning a path through locations that have a high risk of occupancy, and therefore potential delay or collision.

Abstract: A surgical procedure on a patient is monitored at a sensor to provide an observation. A current surgical state is estimated as a belief state over of a plurality of surgical states, representing different phases of the surgery, from the observation and an observation function for each surgical state. A world state of a plurality of world states representing a state of one of the patient, a medical professional performing the surgical procedure, and the environment in which the surgical procedure is being conducted is estimated from the estimated surgical state. From the estimated surgical state, the estimated world state, and a model, at least one surgical state that will be entered during the surgical procedure is predicted and an output representing the predicted at least one surgical state is provided O at an associated output device.

Abstract: A method of non-line-of-sight (NLoS) obstacle detection for an ego vehicle is described. The method includes capturing a sequence of images over a period with an image capture device. The method also includes storing the sequence of images in a cyclic buffer. The method further includes registering each image in the cyclic buffer to a projected image. The method includes performing the registering by estimating a homography H for each frame of the sequence of images to project to a view point of a first frame in the sequence of images and remove motion of the ego vehicle in the projected image. The method also includes enhancing the projected image. The method further includes classifying the projected image based on a scene determination. The method also includes issuing a control signal to the vehicle upon classifying the projected image.

Abstract: The present disclosure provides systems and methods to detect occluded objects using shadow information to anticipate moving obstacles that are occluded behind a corner or other obstacle. The system may perform a dynamic threshold analysis on enhanced images allowing the detection of even weakly visible shadows. The system may classify an image sequence as either “dynamic” or “static”, enabling an autonomous vehicle, or other moving platform, to react and respond to a moving, yet occluded object by slowing down or stopping.

Abstract: System and method to autonomously operate a vehicle during travel are disclosed.

Abstract: An artificial muscle system includes a collapsible skeleton, a flexible skin, and a muscle actuation mechanism. The collapsible skeleton is contained inside a volume defined, at least in part, by the flexible skin. The flexible skin and the collapsible skeleton are configured for the flexible skin to provide a pulling force on the collapsible skeleton when a pressure difference exists between the inside of the sealed volume and a surrounding environment to change at least one of the dimensions and thus geometry of the collapsible skeleton. The muscle actuation mechanism includes at least one of the following to deploy or contract the collapsible skeleton: (a) a fluid displacing, releasing, or capturing mechanism configured to increase or decrease fluid pressure inside the sealed volume; and (b) a heating or cooling element configured to change the temperature of fluid in the sealed volume.

Abstract: Systems and methods described herein relate to estimating risk associated with a vehicular maneuver. One embodiment acquires a geometric representation of an intersection including a lane in which a vehicle is traveling and at least one other lane; discretizes the at least one other lane into a plurality of segments; determines a trajectory along which the vehicle will travel; estimates a probability density function for whether a road agent external to the vehicle is present in the respective segments; estimates a traffic-conflict probability of a traffic conflict in the respective segments conditioned on whether an external road agent is present; estimates a risk associated with the vehicle following the trajectory by integrating a product of the probability density function and the traffic-conflict probability over the at least one other lane and the plurality of segments; and controls operation of the vehicle based, at least in part, on the estimated risk.