Abstract: Variable-grid securing processes, structures produced by variable-grid securing processes, systems for variable-grid securing, and variable-grid-containing structures are disclosed. The variable-grid securing process includes providing members within a first member set and a second member set, and securing a first portion of the members within the first member set to a second portion of the members within the second member set. The securing is based upon predetermined parameters and updated parameters, the updated parameters applying input captured by analyzing the members. Structures produced by the variable-grid securing process and variable-grid-containing structures are produced by the analyzing of the members. The systems for variable-grid securing use the variable-grid securing process.

Abstract: A method and system for autonomous picking or put-away of items, totes, or cases within a logistics facility. The system includes a remote server and at least one manipulation robot. The system may further include at least one transport robot. The remote server is configured to communicate with the various robots to send and receive picking data, and the various robots are configured to autonomously navigate and position themselves within the logistics facility.

Abstract: A method and system for autonomous picking or put-away of items, totes, or cases within a logistics facility. The system includes a remote server and at least one manipulation robot. The system may further include at least one transport robot. The remote server is configured to communicate with the various robots to send and receive picking data, and the various robots are configured to autonomously navigate and position themselves within the logistics facility.

Abstract: A method and system for autonomous picking or put-away of items, totes, or cases within a logistics facility. The system includes a remote server and at least one manipulation robot. The system may further include at least one transport robot. The remote server is configured to communicate with the various robots to send and receive picking data, and the various robots are configured to autonomously navigate and position themselves within the logistics facility.

Abstract: A method and system for picking or put-away within a logistics facility. The system includes a central server and at least one mobile manipulation robot. The central server is configured to communicate with the robots to send and receive picking data which includes a unique identification for each item to be picked, a location within the logistics facility of the items to be picked, and a route for the robot to take within the logistics facility. The robots can then autonomously navigate and position themselves within the logistics facility by recognition of landmarks by at least one of a plurality of sensors. The sensors also provide signals related to detection, identification, and location of a item to be picked or put-away, and processors on the robots analyze the sensor information to generate movements of a unique articulated arm and end effector on the robot to pick or put-away the item.

Abstract: A method and system for autonomous picking or put-away of items, totes, or cases within a logistics facility. The system includes a remote server and at least one manipulation robot. The system may further include at least one transport robot. The remote server is configured to communicate with the various robots to send and receive picking data, and the various robots are configured to autonomously navigate and position themselves within the logistics facility.

Abstract: A method and system for picking or put-away within a logistics facility. The system includes a central server and at least one mobile manipulation robot. The central server is configured to communicate with the robots to send and receive picking data which includes a unique identification for each item to be picked, a location within the logistics facility of the items to be picked, and a route for the robot to take within the logistics facility. The robots can then autonomously navigate and position themselves within the logistics facility by recognition of landmarks by at least one of a plurality of sensors. The sensors also provide signals related to detection, identification, and location of a item to be picked or put-away, and processors on the robots analyze the sensor information to generate movements of a unique articulated arm and end effector on the robot to pick or put-away the item.

Abstract: A method includes acquiring image data from for a given time step. The image data represents at least one of an instrument and a target within an image space that includes patient anatomy. A given belief of system state is estimated to include an estimate of instrument state and target state determined from corresponding measurement and motion models computed based on the acquired image data and control input parameters for the given time step. An expected belief of system state is estimated for a subsequent time step based on the estimated given belief of system state and based on the measurement models and the motion models computed over a plurality of different control inputs parameters. An information metric is computed for each of the expected beliefs of system state and control input parameters are selected for the subsequent time step based on the computed information metrics.

Abstract: A method includes acquiring image data from for a given time step. The image data represents at least one of an instrument and a target within an image space that includes patient anatomy. A given belief of system state is estimated to include an estimate of instrument state and target state determined from corresponding measurement and motion models computed based on the acquired image data and control input parameters for the given time step. An expected belief of system state is estimated for a subsequent time step based on the estimated given belief of system state and based on the measurement models and the motion models computed over a plurality of different control inputs parameters. An information metric is computed for each of the expected beliefs of system state and control input parameters are selected for the subsequent time step based on the computed information metrics.