Abstract: The present disclosure provides methods of producing progenitor cells from induced pluripotent stem cells, wherein the progenitor cells comprise endothelial cells, pericytes, brain microvascular endothelial cells (BMECs), mesenchymal stem cells (MSCs), hematopoietic precursor cells (HPCs), microglia or neural precursor cells (NPCs).

Abstract: A method of planning a path for an articulated arm of robot includes generating a directed graph corresponding to a joint space of the articulated arm. The directed graph includes a plurality of nodes each corresponding to a joint pose of the articulated arm. The method also includes generating a planned path from a start node associated with a start pose of the articulated arm to an end node associated with a target pose of the articulated arm. The planned path includes a series of movements along the nodes between the start node and the end node. The method also includes determining when the articulated arm can travel to a subsequent node or the target pose, terminating a movement of the articulated arm towards a target node, and initiating a subsequent movement of the articulated arm to move directly to the target pose or the subsequent node.

Abstract: Systems and methods related to intelligent grippers with individual cup control are disclosed. One aspect of the disclosure provides a method of determining grip quality between a robotic gripper and an object. The method comprises applying a vacuum to two or more cup assemblies of the robotic gripper in contact with the object, moving the object with the robotic gripper after applying the vacuum to the two or more cup assemblies, and determining, using at least one pressure sensor associated with each of the two or more cup assemblies, a grip quality between the robotic gripper and the object.

Abstract: A system (10) for convolving and adding frames of data comprises a first sensor-display device (14) and a second sensor display device (26). Each sensor display device (14, 26) comprises an array (80) of transmit-receive modules (82). Each transmit-receive module (82) comprises a light sensor element (86), a light transmitter element (84), and a memory bank (90). A radial modulator device (20) is positioned where transmission of light fields comprising frames of data are Fourier transformed. Filters implemented by modulator elements of the radial modulator device (20) convolve the fields of light comprising the frames of data, which are then sensed on a pixel-by-pixel basis by the light sensor elements (86), which accumulate charges, thus sum pixel values of sequential convolved frames of data.

Abstract: A method for palletizing includes receiving a target box location for a box grasped by the end-effector, the box having a top surface, a bottom surface, and side surfaces. The method also includes positioning the box at an initial position adjacent to the target box location and tilting the box at an angle relative to a ground plane where the angle is formed between the ground plane and the bottom surface. The method further includes shifting the box from the initial position in a first direction to a first alignment position that satisfies a threshold first alignment distance, shifting the box from the first alignment position in a second direction to the target box location that satisfies a threshold second alignment distance, and releasing the box from the end-effector. The release of the box causes the box to pivot toward a boundary edge of the target box location.

Abstract: A method includes receiving, while a robot traverses a building environment, sensor data captured by one or more sensors of the robot. The method includes receiving a building information model (BIM) for the environment that includes semantic information identifying one or more permanent objects within the environment. The method includes generating a plurality of localization candidates for a localization map of the environment. Each localization candidate corresponds to a feature of the environment identified by the sensor data and represents a potential localization reference point. The localization map is configured to localize the robot within the environment when the robot moves throughout the environment.

Abstract: A method includes receiving sensor data for an environment about the robot. The sensor data is captured by one or more sensors of the robot. The method includes detecting one or more objects in the environment using the received sensor data. For each detected object, the method includes authoring an interaction behavior indicating a behavior that the robot is capable of performing with respect to the corresponding detected object. The method also includes augmenting a localization map of the environment to reflect the respective interaction behavior of each detected object.

Abstract: Methods, systems, and techniques for generating a new, animation-ready anatomy. A skin mesh of the new anatomy is obtained, such as by performing a 3D depth scan of a subject. Selected template anatomies are also obtained, with each of those template anatomies having a skin mesh that corresponds with the new anatomy's skin mesh. The skin meshes of the new and selected template anatomies share a first pose. Each of the selected template anatomies also has a skeleton for the first pose and skinning weights, and the skin mesh in at least one additional pose that is different from the first pose and any other additional poses. The method then involves using a processor to interpolate, from the at least one of the skeleton and skinning weights of the selected template anatomies and the first and at least one additional pose of the selected template anatomies, the new anatomy.

Abstract: The present disclosure provides methods of producing hepatocytes from induced pluripotent stem cells. Further provided herein are methods of using the hepatocytes for the treatment of a liver disease.

Abstract: A method of footstep contact detection includes receiving joint dynamics for a swing leg of the robot where the swing leg performs a swing phase of a gait of the robot. The method also includes receiving odometry defining an estimation of a pose of the robot and determining whether an unexpected torque on the swing leg corresponds to an impact on the swing leg. When the unexpected torque corresponds to the impact, the method further includes determining whether the impact is indicative of a touchdown of the swing leg on a ground surface based on the odometry and the joint dynamics. When the impact is not indicative of the touchdown of the swing leg, the method includes classifying a cause of the impact based on the odometry of the robot and the joint dynamics of the swing leg.

Abstract: A robotic system includes a body including at least one attachment mechanism configured to removably couple a modular component to the body. The modular component includes at least one movable part operable to move relative to the body when the modular component is attached to the body. The system includes a communication interface coupled to the body and configured to be communicatively coupled to the modular component to receive information relating to the modular component and operation of the at least one movable part. The system includes a control system coupled to the body and the communication interface. The control system is configured to: in response to the modular component being attached to the body, receive the information from the modular component by way of the communication interface, and operate the at least one movable part of the modular component according to the information.

Abstract: A computer-implemented method, executed by data processing hardware of a robot, includes receiving sensor data for a space within an environment about the robot. The method includes receiving, from a user interface (UI) in communication with the data processing hardware, a user input indicating a user-selection of a location within a two-dimensional (2D) representation of the space. The location corresponds to a position of a target object within the space. The method includes receiving, from the UI, a plurality of grasping inputs designating an orientation and a translation for an end-effector of a robotic manipulator to grasp the target object. The method includes generating a three-dimensional (3D) location of the target object based on the received sensor data and the location corresponding to the user input. The method includes instructing the end-effector to grasp the target object using the generated 3D location and the plurality of grasping inputs.

Abstract: A method includes obtaining, from an operator of a robot, a return execution lease associated with one or more commands for controlling the robot that is scheduled within a sequence of execution leases. The robot is configured to execute commands associated with a current execution lease that is an earliest execution lease in the sequence of execution leases that is not expired. The method includes obtaining an execution lease expiration trigger triggering expiration of the current execution lease. After obtaining the trigger, the method includes determining that the return execution lease is a next current execution lease in the sequence. While the return execution lease is the current execution lease, the method includes executing the one or more commands for controlling the robot associated with the return execution lease which cause the robot to navigate to a return location remote from a current location of the robot.

Abstract: A computer-implemented method, when executed by data processing hardware of a robot having an articulated arm and a base, causes data processing hardware to perform operations. The operations include determining a first location of a workspace of the articulated arm associated with a current base configuration of the base of the robot. The operations also include receiving a task request defining a task for the robot to perform outside of the workspace of the articulated arm at the first location. The operations also include generating base parameters associated with the task request. The operations further include instructing, using the generated base parameters, the base of the robot to move from the current base configuration to an anticipatory base configuration.

Abstract: Data processing hardware of a robot performs operations to identify a door within an environment. A robotic manipulator of the robot grasps a feature of the door on a first side facing the robot. When the door opens in a first direction toward the robot, the robotic manipulator exerts a pull force to swing the door in the first direction, a leg of the robot moves to a position that blocks the door from swinging in the second direction, the robotic manipulator contacts the door on a second side opposite the first side, and the robotic manipulator exerts a door opening force on the second side as the robot traverses a doorway corresponding to the door. When the door opens in a second direction away from the robot, the robotic manipulator exerts the door opening force on the first side as the robot traverses the doorway.

Abstract: A computer-implemented method, executed by data processing hardware of a robot, includes receiving a three-dimensional point cloud of sensor data for a space within an environment about the robot. The method includes receiving a selection input indicating a user-selection of a target object represented in an image corresponding to the space. The target object is for grasping by an end-effector of a robotic manipulator of the robot. The method includes generating a grasp region for the end-effector of the robotic manipulator by projecting a plurality of rays from the selected target object of the image onto the three-dimensional point cloud of sensor data. The method includes determining a grasp geometry for the robotic manipulator to grasp the target object within the grasp region. The method includes instructing the end-effector of the robotic manipulator to grasp the target object within the grasp region based on the grasp geometry.

Abstract: A computer-implemented method when executed by data processing hardware of a legged robot causes the data processing hardware to perform operations including receiving sensor data corresponding to an area including at least a portion of a docking station. The operations include determining an estimated pose for the docking station based on an initial pose of the legged robot relative to the docking station. The operations include identifying one or more docking station features from the received sensor data. The operations include matching the one or more identified docking station features to one or more known docking station features. The operations include adjusting the estimated pose for the docking station to a corrected pose for the docking station based on an orientation of the one or more identified docking station features that match the one or more known docking station features.

Abstract: A computer-implemented method includes generating a joint-torque-limit model for the articulated arm based on allowable joint torque sets corresponding to a base pose of the base. The method also include receiving a first requested joint torque set for a first arm pose of the articulated arm and determining, using the joint-torque-limit model, an optimized joint torque set corresponding to the first requested joint torque set. The method also includes receiving a second requested joint torque set for a second arm pose of the articulated arm and generating an adjusted joint torque set by adjusting the second requested joint torque set based on the optimized joint torque set. The method also includes sending the adjusted joint torque set to the articulated arm.

Abstract: A computer-implemented method executed by data processing hardware of a robot causes the data processing hardware to perform operations. The robot includes an articulated arm having an end effector engaged with a constrained object. The operations include receiving a measured task parameter set for the end effector. The measured task parameter set includes position parameters defining a position of the end effector. The operations further include determining, using the measured task parameter set, at least one axis of freedom and at least one constrained axis for the end effector within a workspace. The operations also include assigning a first impedance value to the end effector along the at least one axis of freedom and assigning a second impedance value to the end effector along the at least one constrained axis. The operations include instructing the articulated arm to move the end effector along the at least one axis of freedom.

Abstract: A method for terrain and constraint planning a step plan includes receiving, at data processing hardware of a robot, image data of an environment about the robot from at least one image sensor. The robot includes a body and legs. The method also includes generating, by the data processing hardware, a body-obstacle map, a ground height map, and a step-obstacle map based on the image data and generating, by the data processing hardware, a body path for movement of the body of the robot while maneuvering in the environment based on the body-obstacle map. The method also includes generating, by the data processing hardware, a step path for the legs of the robot while maneuvering in the environment based on the body path, the body-obstacle map, the ground height map, and the step-obstacle map.