Abstract: A method and system for creating a high-fidelity depiction of a scene including an object within the scene are provided. The method includes uniformly illuminating a target surface of the object with light to obtain reflected, backscattered illumination. The method also includes sensing via a volumetric sensor, brightness of the surface due to a diffuse component of the backscattered illumination to obtain brightness information. Backscattered illumination from the target surface is inspected to obtain geometric measurements which include sensor noise. Rotationally and positionally invariant measured surface albedo including albedo noise of the object is computed based on the brightness and the geometric measurements. A machine-learning model such as a diffusion sensor model is applied to the geometric measurements and the measured surface albedo to remove the sensor noise and the albedo noise, respectively, to obtain a prediction of actual geometry and actual albedo, respectively, of the object.

Abstract: An end effector device and system for suction-based grasping of bagged objects that can include a body structure with a vacuum line opening and an object engagement region, the vacuum line opening being configured to couple at least one pressure line of a vacuum pressure system to a defined internal channel of the body structure; the body structure comprising an internal structure that defines a concave inner chamber with a chamber opening at the object engagement region; and the internal structure comprising an array of inlets positioned along at least one wall of the concave inner chamber, wherein each inlet defines an opening in the body to the defined internal channel.

Abstract: A method includes: receiving a message, via a communication link, including sensor data in a data stream from a sensor device and first reference data based on a deterministic function and a seed value; extracting the first reference data from the message; generating second reference data based on the deterministic function and the seed value; calculating a first quantity of bit errors in the first reference data based on the second reference data; calculating a bit error rate of the communication link based on the first quantity of bit errors; in response to the bit error rate exceeding a bit error rate threshold for the data stream, generating a second message representing a fault; and transmitting the second message to a second device.

Abstract: A robotic kitchen system for preparing food items in combination with at least one kitchen appliance such as a fryer comprises an automated bin assembly, a robotic arm, and a basket held by the robotic arm. The automated bin assembly comprises at least one automated bin for holding the food items. A camera or sensor array collects image data of the food items in the bin(s). A central processor is operable to compute and provide directions to the first robotic arm and automated bin assembly based on the image data and stored data to (a) move the robotic arm to the bin; (b) actuate the bin to drop the food items from the bin into the basket; (c) and to move the basket into the fryer all without human interaction. Related methods are also described.

Abstract: An end effector device and system for suction-based grasping of bagged objects that can include a body structure with a vacuum line opening and an object engagement region, the vacuum line opening being configured to couple at least one pressure line of a vacuum pressure system to a defined internal channel of the body structure; the body structure comprising an internal structure that defines a concave inner chamber with a chamber opening at the object engagement region; and the internal structure comprising an array of inlets positioned along at least one wall of the concave inner chamber, wherein each inlet defines an opening in the body to the defined internal channel. The body structure may additionally include a suction cup system that comprises a flexible sealing lip at the object engagement region; wherein the chamber opening being positioned within a grasping region of the sealing lip.

Abstract: Devices, systems, and methods for determining whether a container is empty in the context of robotic picking solutions. The system includes a plurality of sensors configured to gather container data regarding a container at a first location, wherein the container data includes at least two of weight data related to the container, depth data related to the container, and color sensor data related to the container, and a processor configured to execute instructions stored on a memory to provide a sensor fusion module configured to process the received container data to determine whether the container is empty.

Abstract: A legged robot has legs that have multiple links, one of which is a distal link. A foot assembly for interacting with the terrain is disposed on a distal end of the distal link. As a robot takes a step, a portion of the foot assembly that has lower effective inertia than the rest of the foot assembly touches down first and acts to reduce the vertical velocity of the rest of the foot assembly before it reaches the terrain through the use of an actuator located on the distal or intermediate link.

Abstract: One variation of a method for tracking and maintaining inventory in a store includes: accessing a image of an inventory structure in the store; identifying a top shelf, in the inventory structure, depicted in the image; identifying a set of product units occupying the top shelf based on features detected in the image; identifying a second shelf, in the set of shelves in the inventory structure, depicted in the image, the second shelf arranged below the top shelf in the inventory structure; based on features detected in the image, detecting an understock condition at a slot—assigned to a product type—on the second shelf; and, in response to the set of product units comprising a product unit of the product type, generating a prompt to transfer the product unit of the product type from the top shelf into the slot on the second shelf at the inventory structure.

Abstract: A feedback-diverse, dual-controller-architecture functional safety system includes: a first module; a second module; and an inter-module logic.

Abstract: A driving simulator can include one or more input devices; a display; and one or more processors communicatively coupled with the one or more input devices and the display. The one or more processors can be configured to store, in memory, a predetermined path for a simulated vehicle to travel in a simulated environment; execute an application to cause the simulated environment to appear on the display in a autonomous mode in which the application is configured to simulate the simulated vehicle driving by updating the display over time according to the predetermined path; receive an input from at least one of the one or more input devices; and responsive to receiving the input, change the mode of the application from the autonomous mode to a manual mode in which the application is configured to update the display according to inputs from the one or more input devices.

Abstract: A system can include a driving simulator. The driving simulator can include one or more input devices corresponding to controls of a vehicle; a display; and one or more processors communicatively coupled with the one or more input devices and the display. The one or more processors can be configured to simulate, on the display, an autonomous vehicle driving through a simulated environment in a manual mode based on inputs from the one or more input devices, automatically in an autonomous mode, and transition between manual mode and autonomous mode. The system can include a remote computing device. The remote computing device can be configured to receive an input from a user interface displayed at the remote computing device during a simulation of the autonomous vehicle in the autonomous mode, the input causing a fault in the operation of the autonomous vehicle in the autonomous mode.

Abstract: Disclosed herein are methods and systems to avoid collisions with animals. In an example, a method comprises receiving, by a processor, an indication that a current trajectory of an autonomous vehicle is associated with a likelihood of a collision that satisfies a collision threshold indicating a potential collision with an animal having an attribute that satisfies a threshold; disabling, by the processor, at least one lighting apparatus associated with the autonomous vehicle; and enabling, by the processor, a sound-generating device associated with the autonomous vehicle.

Abstract: An autonomous tool including a multi-sensor package enabling identification of the position of the tool in a construction site so that the tool may navigate to locations where tasks are performed. The tool may include at least one sensor from the group of a drive system encoder, stereo camera, inertial measurement unit, optical flow sensor, and LiDAR. The tool may include a holonomic drive allowing at least one tool of the mobility platform to reach the extremities of a construction site. The platform may be used as part of a system that receives design information relating to the construction site and tasks to be performed by the tool and then generates commands that control the tool to navigate along a path generated to include landmarks within range of and therefore detectable by the sensors for a large percentage of the path.

Abstract: Systems for assessment of weld adjacent heat affected zones are described. An example system may include an inspection robot having a first payload comprising a first plurality of ultrasonic (UT) phased arrays, and a second payload comprising a second plurality of ultrasonic (UT) phased arrays. The inspection robot is configured to move in a direction of travel corresponding to a weld of an inspection surface, and the first payload is structured to measure characteristics of a first region of the inspection surface on a first side of the weld while the second payload is structured to measure characteristics of a second region of the inspection surface on a second side of the weld.

Abstract: A system includes an article supply location, wherein the article supply location includes a plurality of articles to be sorted, first and second transport vehicles, each having a first position in which an article is stowed about the vehicle and a second position in which the article is deposited into a proximal container. And a control system. The control system is configured to receive an order for a plurality of disparate articles, determine one destination container of a plurality of destination containers to direct the transport vehicle to deposit a selected article, direct the first transport vehicle to transport a selected article to the destination container and deposit the article by manipulation of the first transport vehicle from the first position to the second position for deposit of the selected article in the destination container.

Abstract: In some examples, an autonomous robotic welding system comprises a workspace including a part having a seam, a sensor configured to capture multiple images within the workspace, a robot configured to lay weld along the seam, and a controller. The controller is configured to identify the seam on the part in the workspace based on the multiple images, plan a path for the robot to follow when welding the seam, the path including multiple different configurations of the robot, and instruct the robot to weld the seam according to the planned path.

Abstract: Systems and methods are provided for identifying a vehicle subject to an emergency alert. The method includes receiving an emergency alert, wherein the emergency alert includes a geographic region associated with the emergency alert and one or more identifiable markers of a wanted vehicle, determining whether the autonomous vehicle is within the geographic region associated with the emergency alert, and detecting, using one or more detection mechanisms coupled to the autonomous vehicle, a detected vehicle within an environment of the autonomous vehicle. The method further includes, when the autonomous vehicle is within the geographic region associated with the emergency alert, determining, for each identifiable marker, whether the detected vehicle matches the identifiable marker, and when the detected vehicle matches the one or more identifiable markers, generating, using a processor coupled to the autonomous vehicle, a signal indicating that the detected vehicle is the wanted vehicle.

Abstract: Systems and methods for surface fitting of a surface of an object, for path planning, and for processing a surface of a part are disclosed. The method includes receiving, at a processor, a point cloud or a mesh of the surface; dividing, by the processor, the point cloud to a plurality of overlapping sub-patches; determining by the processor, a first Root Mean Squared Error (RMSE) of the overall surface; and in response to the first RMSE being smaller or equal to the user set RMSE, generating, by the processor, coefficients for characterizing the surface.

Abstract: Embodiments described herein include a system of fluid-delivery hardware, including tubes, valves, and pumps that deliver samples of fluid gathered from various exposed locations of a vehicle to commonly located gas analysis sensors. A durable sensor housing contains the gas sensors and is situated in a confined location of the vehicle, which is environmentally isolated and physically partitioned from the sample locations exposed to potentially deleterious environments. For a given sample location, a tube and valves gather and channel fluid samples from the sample location towards the sensor housing at the confined location. A pump forces air outwards to purge debris in the tube or tube inlet, and draws air inward through the tube towards the sensor housing for delivery to the sensors.

Abstract: Systems and methods for training artificial intelligence models based on sequences of image data are disclosed. The techniques described herein include generating, using an artificial intelligence model, a respective classification and a respective bounding box for an object depicted in each image of a sequence of images captured during operation of an autonomous vehicle; tracking the object in the sequence of images based on the respective bounding box of each image of the sequence of images and a tracking identifier corresponding to the object; determining a correction to the respective classification of an image of the sequence of images responsive to tracking the object in the sequence of images; and training the artificial intelligence model based on the correction.