A manufacturing system including an automated storage and retrieval system (ASRS) structure with a three-dimensional array of storage locations distributed throughout a two-dimensional footprint of the ASRS structure at multiple storage levels; workpieces stored within the storage locations of the ASRS structure; robotic storage retrieval vehicles (RSRVs) navigable within the ASRS structure in three dimensions to access the storage locations, and multiple manufacturing cells positioned outside the ASRS structure, is provided. The manufacturing system includes a track structure attached to the ASRS structure and defining one or more travel paths traversable by the RSRVs from the ASRS structure. The same fleet of RSRVs that is navigable within the ASRS structure is operable to deliver the workpieces to the manufacturing cells. One or more of the manufacturing cells are positioned along the track structure, thereby receiving convenient access to the workpieces along with associated tool pieces and workpiece supports for manufacturing goods.

A robot arm control device according to the present disclosure comprises a workpiece selecting section that selects a target workpiece, which is a workpiece to be picked up and placed, among a plurality of workpieces conveyed by a conveyor system in a predetermined flow direction; and a motion control section that controls a motion of the robot arm to pick up the target workpiece at a predetermined pick up position and place the target workpiece at the target placement position selected among a plurality of predetermined placement positions, wherein the workpiece selecting section selects, among the workpieces that are candidates for selection, the workpiece that has a shortest distance from the distal end position at a task-start timing to the workpiece position at the task-start timing as the target workpiece.

A joist assembly system that is structured for dynamic retrieval of components, dynamic and precise positioning and location of retrieved components, assembly of the components to form a joist, and delivery of the assembled joist. The joist assembly system has a plurality of material handling systems, a plurality of welding systems, and a rigging table system. The material handling systems are structured to load and position the components such as chords and webs onto the rigging table. The rigging table in turn supports the chords or webs. Subsequently, the plurality of welding systems weld the webs to the chords to form the joist.

An automation server accesses a task for a robotic device. The automation server generates motor control commands for the robotic device to complete the task. The automation server transmits, via a network and in a format defined by an Application Program Interface (API), the motor control commands from the automation server to a fleet manager associated with the robotic device, the motor control commands for forwarding from the fleet manager to the robotic device. The automation server receives, from one or more sensors attached to the robotic device and via the network, robotic device sensor data. The automation server receives, from multiple remote sensors and via the network, remote sensor data. The automation server adjusts the generated motor control commands to complete the task based on the robotic device sensor data and the remote sensor data.

A coffee machine includes a housing that comprises a first platform, a second platform, a first robotic arm, a second robotic arm, and an information handling system. The information handling system comprises a memory and a processor. The memory is configured to receive and store a multiple beverage orders in a log and to monitor a position of a first cup and a second cup corresponding to a first beverage order and a second beverage order. The processor is configured to initiate a second sub-step of the second beverage order prior to initiating a second sub-step of the first beverage order in response to determining that a first sub-step of the second beverage order has terminated first and to transmit to the log of the memory that the second cup is at the third designated position for the second sub-step of the second beverage order to be performed.

A coffee machine includes a first housing and a second housing, wherein the second housing is disposed on top of the first housing. The second housing comprises a first platform, a second platform disposed below the first platform, and a lift disposed at a first side of the second housing and configured to translate between the first platform and the second platform. The second housing further comprises a first robotic arm disposed above the first platform, a second robotic arm disposed between the second platform and the first platform, and a coffee brewing machine actionable to dispense one or more fluids into a cup. The coffee machine further comprises an information handling system comprising a processor, wherein the processor is configured to actuate the first robotic arm, the second robotic arm, the coffee brewing machine, and the lift.

Disclosed is a dual-robot position/force multivariate-data-driven method using reinforcement learning. A master robot adopts an ideal position meta-control strategy, learns a desired position by a reinforcement learning algorithm, and feeds back an actual position to a desired position, and a goal is to generate an optimal force while the robot interacts with the environment, as to minimize a position error; and a slave robot, based on a force meta-control strategy of position deviation of the master robot, adopts a damping proportional-derivative (PD) control strategy suitable for an unknown environment, and learns a desired acting force by the reinforcement learning algorithm, namely a minimum force for driving the slave robot to approach a desired reference point. The present invention may improve the dexterity of dual-robot collaboration, solve a parameter optimization problem in position/force control.

A centering device (1) for centering flat workpieces (700-706) comprises a centering station (100) having at least a first and a second gripping device (300, 301) for gripping the workpiece (700-706), and conveying means for conveying workpieces (700-706) in a conveying direction to the centering station (100). The first and the second gripping device (300, 301) can each be moved horizontally by a first and a second guiding device (200, 201), respectively, and the first and the second gripping device (300, 301) can rotate freely about an axis.

Increased robotic sophistication and more efficient autonomous operation is implemented by providing separate physical autonomous robots shared and remote access to the sensory array and information from the sensory array of one another. Each robot can access a sensor of any other robot, or scans or other information obtained from the sensor of any other robot. The robots leverage the shared sensory access in order to perform batch order fulfillment, dynamic rearrangement of item or tote locations, and opportunistic charging. These coordinated robotic operations based on the shared sensory access increase the efficiency and productivity of the robots without adding resources or hardware to the robots, increasing the speed of the robots, or increasing the number of deployed robots.

Approaches presented herein enable maneuvering collaborative robots to rescue persons in a hydrological disaster. A plurality of robots are dispersed in a body of water to spread out and seek victims using cooperative foraging techniques within resource constraints. A location of victims located by a robot using sensing techniques is communicated to other robots. A situational assessment is performed using victim location information to determine a number of robots to deploy to the location. The deployed robots are directed to perform coordinated maneuvers to create a connected floatation unit to support floatation of victims for rescue.