A system includes a controller to provide at least one control output to an automated system in response to a control command received at a control input of the controller. The control output controls the operation of the automated system based on the control command. A signature analyzer generates the control command to the controller and receives an impedance signature related to a property of a material or object encountered by the automated system. The signature analyzer compares the impedance signature to at least one comparison signature to determine the property of the material or object. The signature analyzer adjusts the control command to the controller to control the operation of the automated system based on the determined property.

A controller for a parallel link mechanism includes a drive control unit that controls driving of a parallel link mechanism and a command section that gives a command for controlling an actuator to the drive control unit. The command section includes a natural frequency prediction unit that calculates a predicted value string of a natural frequency changing depending on the position of an end effector for each interpolation position of the end effector by using a dynamic model that simulates a mechanical system from a base to a link joint of the parallel link mechanism with a translational spring and simulates a mechanical system from the link joint to the end effector with one rigid body. The drive control unit includes a filter that changes a frequency component to be suppressed for each interpolation positions according to a predicted value string at each interpolation position of the end effector.

In one embodiment, the present disclosure includes a cloud computer system for controlling a plurality of remote devices comprising a cloud server including a cloud based operating system comprising a data model stored in a computer memory. The data model includes commands that may be performed by a plurality of remote devices in a remote system and, for each remote device, one or more operations for triggering processes executed by the remote device. The cloud based operating system generates a set of instructions from the plurality of commands and corresponding operations to control a portion of the remote devices to perform a task.

A method of operating a robot includes acquiring a first condition that defines a given model work, acquiring for the model work, conversion information for acquiring first corrected operation information based on first temporary operation information of the robot, acquiring a second condition that defines a given target work, and acquiring second corrected operation information indicative of corrected operation of the robot for the target work based on the first condition, the second condition, and the conversion information.

In one embodiment, the present disclosure includes an automated delivery system apparatus comprising a mechanical guide, a movable unit coupled to the guide on a first surface, and an engaging unit configured to couple to a second surface separated from the first surface by a thickness. The engaging unit is configured to engage an item on the second surface. A magnetic binding force between the movable unit and engaging unit moves the engaging unit along a path corresponding to a path of the movable unit. The engaging unit moves an item along a least a portion of the path.

In one embodiment, the present disclosure includes a granule dispenser comprising a container for holding granulated components, a cap coupled to a bottom of said container, and a stopper. The stopper may be spring loaded against the ridge of said cap. An interface between the stopper and the cap comprises a plurality of protrusions and a plurality of sawtooth forms, wherein the protrusions mate to a base portion between the sawtooth forms in a first position to form a seal between the cap and the stopper, and wherein, when the stopper is rotated, the protrusions engage a sloped portion of the sawtooth forms to create a plurality of openings between the cap and the stopper.

In one embodiment, the present disclosure includes an automated food production kiosk. Embodiments of a kiosk may comprise a robotic system having a reach. A plurality of food ingredient dispensers may be configured around the robotic system. Each dispenser may have a physical interface within a reach of the robotic system to receive an item. One or more physical processing units have a physical interface within the reach of the robotic system to receive the item. The kiosk may prepare food items under control of a local server, a cloud server, or both, for example.

In one embodiment, the present disclosure includes a solid dispenser comprising a dispensing element and a housing. The dispensing element includes a plurality of blades extending from a cylindrical base. In one example embodiment, the blades are separated by 90 degrees to form channels from an upper opening in the housing to a lower opening in the housing. A hopper for storing items to be dispensed may be configured on one side of the dispenser, and a trap for controlling the flow of dispensed items may be configured on the other side of the dispenser. In one embodiment, the dispenser is controlled by motors coupled to a server as part of a fully automated cloud controlled robotic food preparation system, where each dispenser may accurately deliver different quantities of ingredients for different orders.

In one embodiment, the present disclosure includes a cloud computer system for controlling a plurality of remote devices comprising a cloud server including a cloud based operating system comprising a data model stored in a computer memory. The data model includes commands that may be performed by a plurality of remote devices in a remote system and, for each remote device, one or more operations for triggering processes executed by the remote device. The cloud based operating system generates a set of instructions from the plurality of commands and corresponding operations to control a portion of the remote devices to perform a task.

Described herein is a framework for efficient task-agnostic, user-independent adaptive teleoperation of mobile robots and remotely operated vehicles (ROV), including ground vehicles (including legged systems), aircraft, watercraft and spacecraft. The efficiency of a human operator is improved by minimizing the entropy of the control inputs, thereby minimizing operator energy and achieving higher performance in the form of smoother trajectories by concurrently estimating the user intent online and adaptively updating the action set available to the human operator.