Abstract: Methods, systems, and techniques are disclosed for selecting and dispatching a worker to assist a robot. The system may include a computer comprising a processor and a computer readable memory. The computer readable memory may include lists of worker criteria items for a plurality of workers and a list of assistance criteria items for a robot. The system may include a triggering application executable by the processor for identifying triggering data corresponding to a triggering item within sensor data from the robot. A ranking application may also be stored on the computer and may be executed in response to an identification of triggering data corresponding to the triggering item. The ranking application may be operable to cross-reference the worker criteria items on each of the first lists with the assistance criteria items on the second list and to generate a ranking of the plurality of workers based on the cross-referencing.

Abstract: A method of operating an exoskeleton system that includes determining a first state estimate for a current classification program being implemented by the exoskeleton system; determining a second state estimate for a reference classification program; determining that a difference between the first and second state estimate is greater than a classification program replacement threshold; generating an updated classification program; and replacing the current classification program with the updated classification program based at least in part on the determining that the difference between the first and second state estimates is greater than the classification program replacement threshold.

Abstract: A method for controlling movement of a robot includes inputting a first linear velocity parameter and a first angular velocity parameter, which are specified as the robot moves, into a first limit model for limiting a centripetal acceleration to correct the first linear velocity parameter and the first angular velocity parameter, thereby calculating a second linear velocity parameter and a second angular velocity parameter, inputting the second linear velocity parameter and the second angular velocity parameter into at least one of a second limit model for limiting a linear velocity and a third limit model for limiting an angular velocity to correct the second linear velocity parameter and the second angular velocity parameter, thereby calculating a third linear velocity parameter and a third angular velocity parameter, and controlling the movement of the robot based on the third linear velocity parameter and the third angular velocity parameter.

Abstract: A high-speed low runout spindle assembly is provided. The spindle assembly includes a friction drive wheel configured to be coupled to an output shaft of a motor. The friction drive wheel is configured and disposed to directly contact a shank of a bit. A set of bearings is configured to contact the shank of the bit. A bit clamp assembly includes a clamp bearing having a central through-hole dimensioned to accept a lower portion of the shank of the bit. The bit clamp assembly is configured to hold the bit in contact with the set of bearings.

Abstract: One variation of a method for managing virtual shopping lists includes: dispatching robotic systems, deployed in store, to autonomously scan inventory structures within this store; deriving current stock conditions of this store based on scan data recorded by these robotic systems; initializing a virtual shopping list for a user; in response to receipt of selection of a first product, from a population of products, isolating a subset of stores, in the set of stores in the geographic region, associated with current stock conditions indicating presence of the first product and products previously added to the virtual shopping list; in response to the subset of stores including at least one store, adding a first identifier of the first product to the virtual shopping list; and specifying a particular store, in the subset of stores, for fulfillment of a set of products on the virtual shopping list.

Abstract: Systems and methods for optimizing factory scheduling, layout or both which represent active factory elements (human and machine) as computational objects and simulate factory operation to optimize a solution. This enables the efficient assembly of customized products, accommodates variable demand, and mitigates unplanned events (floor blockages, machines/IMRs/workcell/workers downtime, variable quantity, location, and destination of supply parts).

Abstract: Embodiments of the present invention provide automated robotic system identification and stopping time and distance estimation, significantly improving on existing ad-hoc methods of robotic system identification. Systems and methods in accordance herewith can be used by end users, system integrators, and the robot manufacturers to estimate the dynamic parameters of a robot on an application-by-application basis.

Abstract: Systems and methods for providing inter-vehicle communication are disclosed. The method includes receiving, at a fleet management system, operating data from one or more self-driving vehicles via a communication network, and operating the fleet management system to determine a characteristic of a set of vehicles of one or more self-driving vehicles satisfies at least one communication condition. In response to determining the set of vehicles satisfies the at least one communication condition, the fleet management system can operate to select a stored data portion from a manager storage unit based at least on the characteristic of the set of vehicles; and transmit the data portion to the set of vehicles via the communication network. A method of providing inter-vehicle communication between one or more self-driving vehicles is also disclosed.

Abstract: An inventory verification device (“IVD”) provides automatic inventory verification and detection of inventory discrepancies. The IVD automatically verifies the quantity of items in a container based on weight and/or height measurements obtained for the items in the container using two or more sensors of the IVD. The IVD may also automatically updated tracked inventory of an item based on detected changes to the weight and/or height of the items in the container as a result of a worker adding items to the container or removing items from the container without the working providing confirmation for each addition and/or removal. The IVD autoatmically verifies whether correct items are stored in a container by performing feature matching of various characteristics for items imaged in the container against expected characteristics for items that should be stored in the container.

Abstract: There is disclosed a rotary actuator apparatus for hydraulically or pneumatically rotating a robotic joint. In an embodiment the apparatus comprises: a curved piston rotatably coupled to an axel shaft, and positioned within a curved piston chamber; resilient barrier modules are adapted to separate the curved piston within the curved piston chamber from first and second hydraulic or pneumatic chambers on either side of the curved piston chamber; whereby, in use, the curved piston is configured to rotate about the axel shaft upon hydraulic or pneumatic pressure being applied to at least one of the first and second hydraulic or pneumatic chambers.

Abstract: System for guiding an instrument within a vascular network of a patient are disclosed. In some embodiments, the system receives a medical image from a medical imaging device and identifies a distal tip and a direction the instrument in the image. The system may then determine a waypoint for the distal tip of the instrument based at least in part on the position and direction of the distal tip of the instrument. The system may then generate a trajectory command for moving the instrument through the vascular network from the current position to the waypoint. The system may operate in a closed loop. The system may provide the trajectory command to a robotic medical system configured to move the instrument according to the command.

Abstract: Exemplary embodiments relate to improvements in robotic systems to reduce biological or chemical harborage points on the systems. For example, in exemplary embodiments, robotic actuators, hubs, or entire robotic systems may be configured to allow crevices along joints or near fasteners to be reduced or eliminated, hard corners to be replaced with rounded edges, certain components or harborage points to be eliminated, shapes to be reconfigured to be smoother or flat, and/or or surfaces to be reconfigurable for simpler cleaning.

Abstract: A method of generating robot trajectories for a robot device includes generating surface parameters and/or measurements for the surface of the object; receiving one or more parameters to maximize or minimize robot objectives; receiving one or more motion parameters for the robot to perform the task on the surface of the object and/or receiving one or more workspace parameters; receiving a plurality of constraint parameters; and generating an initial parametric representation of a trajectory for the robot in performing the task. The method further includes generating an initial trajectory based on the initial parametric representation of the trajectory, one or more workspace parameters, the one or more motion parameters, and/or the one or more parameters to maximize or minimize robot objectives; selecting a first set of constraint parameters; and performing trajectory generation by applying the selected first set of constraint parameters to create one or more first robot trajectories.

Abstract: Systems, apparatus, and methods are described for robotic learning and execution of skills. A robotic apparatus can include a memory, a processor, sensors, and one or more movable components (e.g., a manipulating element and/or a transport element). The processor can be operatively coupled to the memory, the movable elements, and the sensors, and configured to obtain information of an environment, including one or more objects located within the environment. In some embodiments, the processor can be configured to learn skills through demonstration, exploration, user inputs, etc. In some embodiments, the processor can be configured to execute skills and/or arbitrate between different behaviors and/or actions. In some embodiments, the processor can be configured to learn an environmental constraint. In some embodiments, the processor can be configured to learn using a general model of a skill.

Abstract: An autonomous earth moving system can determine a desired state for a portion of the EMV including at least one control surface. Then the EMV selects a set of control signals for moving the portion of the EMV from the current state to the desired state using a machine learning model trained to generate control signals for moving the portion of the EMV to the desired state based on the current state. After the EMV executes the selected set of control signals, the system measures an updated state of the portion of the EMV. In some cases, this updated state of the EMV is used to iteratively update the machine learning model using an online learning process.

Abstract: A computing device generates a graphical user interface displaying a three-dimensional representation of the site comprising a position of a vehicle capable of moving material within the site and a target location within the site for the vehicle to move material. The computing device transmits a set of instructions for the vehicle to move a volume of material from the target location. The computing device receives sensor data describing a depth of the target location, a current volume of material moved from the target location, and a position of the vehicle. The graphical user interface displayed on the computing device is modified to display the current depth of the target location, and the position of the vehicle relative to the target location. The computing device modifies the set of instructions based on the received sensor data and provides the modified set of instructions to the vehicle.

Abstract: Systems and methods for monitoring a fleet of self-driving vehicles are disclosed. The system comprises one or more self-driving vehicles having at least one sensor for collecting current state information, a fleet-management system, and computer-readable media for storing reference data. The method comprises autonomously navigating a self-driving vehicle in an environment, collecting current state information using the vehicle's sensor, comparing the current state information with the reference data, identifying outlier data in the current state information, and generating an alert based on the outlier data. A notification based on the alert may be sent to one or more monitoring devices according to the type and severity of the outlier.

Abstract: A robot control system determines which of a number of discretizations to use to generate discretized representations of robot swept volumes and to generate discretized representations of the environment in which the robot will operate. Obstacle voxels (or boxes) representing the environment and obstacles therein are streamed into the processor and stored in on-chip environment memory. At runtime, the robot control system may dynamically switch between multiple motion planning graphs stored in off-chip or on-chip memory. The dynamically switching between multiple motion planning graphs at runtime enables the robot to perform motion planning at a relatively low cost as characteristics of the robot itself change.