Abstract: A method for fabricating a multi-material structure includes: forming a structural member with at least one open-cell void that is formed on a surface of the structural member; depositing a first portion of a polymeric skin on the surface; and depositing a second portion of the polymeric skin within the at least one open-cell void.

Abstract: A computer-implemented method for controlling a machine includes: determining a first state for the machine based on a kinematics model of the machine and a target roto-translation for an end effector associated with the machine; determining, using a forward-kinematics machine-learning model, a difference between the target roto-translation of the end effector and a first roto-translation of the end effector when the machine is in the first state; based on the difference between the target roto-translation and the first roto-translation, determining a second state for the machine; and outputting a control input for one or more actuators that causes the machine enter into the second state.

Abstract: A multi-material structure includes: a structural member that includes an isotropic material and at least one open-cell void formed in the isotropic material; and a skin that includes a polymetric material and is disposed on a surface of the structural member and within the at least one open-cell void.

Abstract: A computer-implemented method for generating a forward-kinematics machine-learning (ML) model for controlling a machine includes: based on a target state for the machine, determining an ideal roto-translation for an end effector associated with the machine; using a first version of the forward-kinematics ML model, determining a predicted roto-translation for the end effector based on the target state; determining a predicted location for at least one calibration point on the end effector based on the predicted roto-translation for the end effector; determining a difference between the predicted location for the at least one calibration point and a measured location for the at least one calibration point; and generating a second version of the forward-kinematics ML model based on the difference.