Abstract:
A device for gripping a workpiece is described, and includes a holder including a base and a conformable jamming element. The conformable jamming element includes an air-impermeable pliable membrane containing filling material including magnetic particles, and is attached to the base. An electroadhesive element and a conformable releasable surface-adhesive element are secured to a surface of the membrane.
Abstract:
A gripping device is described and includes a holder including a base and a conformable jamming element that has a conformable releasable surface-adhesive element secured onto its surface.
Abstract:
A system includes host and learning machines. Each machine has a processor in electrical communication with at least one sensor. Instructions for predicting a binary quality status of an item of interest during a repeatable process are recorded in memory. The binary quality status includes passing and failing binary classes. The learning machine receives signals from the at least one sensor and identifies candidate features. Features are extracted from the candidate features, each more predictive of the binary quality status. The extracted features are mapped to a dimensional space having a number of dimensions proportional to the number of extracted features. The dimensional space includes most of the passing class and excludes at least 90 percent of the failing class. Received signals are compared to the boundaries of the recorded dimensional space to predict, in real time, the binary quality status of a subsequent item of interest.
Abstract:
A system includes host and learning machines. Each machine has a processor in electrical communication with at least one sensor. Instructions for predicting a binary quality status of an item of interest during a repeatable process are recorded in memory. The binary quality status includes passing and failing binary classes. The learning machine receives signals from the at least one sensor and identifies candidate features. Features are extracted from the candidate features, each more predictive of the binary quality status. The extracted features are mapped to a dimensional space having a number of dimensions proportional to the number of extracted features. The dimensional space includes most of the passing class and excludes at least 90 percent of the failing class. Received signals are compared to the boundaries of the recorded dimensional space to predict, in real time, the binary quality status of a subsequent item of interest.
Abstract:
A system includes host and learning machines in electrical communication with sensors positioned with respect to an item of interest, e.g., a weld, and memory. The host executes instructions from memory to predict a binary quality status of the item. The learning machine receives signals from the sensor(s), identifies candidate features, and extracts features from the candidates that are more predictive of the binary quality status relative to other candidate features. The learning machine maps the extracted features to a dimensional space that includes most of the items from a passing binary class and excludes all or most of the items from a failing binary class. The host also compares the received signals for a subsequent item of interest to the dimensional space to thereby predict, in real time, the binary quality status of the subsequent item of interest.
Abstract:
A part formation system includes: a mobile robot; a first material feeding device configured to feed carbon fiber prepreg material, one layer at a time, onto the mobile robot to form a stack of carbon fiber prepreg layers on the mobile robot; a second material feeding device configured to feed a paint film onto the stack of carbon fiber prepreg layers to provide a resultant stack of layers; and a heat press configured to form and cure the resultant stack of layers to provide a resultant painted part by heating and compressing the resultant stack of layers.
Abstract:
A robotic system is provided. The robot system includes a robot arm, a lamp assembly, and a control module. The robot arm includes a first end and a second end that opposes the first end. The lamp assembly is disposed at the second end of the robot arm and includes at least one ultraviolet (UV) light that is configured to cure paint on a panel of a vehicle. The control module is configured to actuate the robot arm and position the lamp assembly relative to the panel of the vehicle.
Abstract:
An overspray-free paint system includes: a paint robot including an overspray-free paint applicator; and a first fixture robot for lifting and orienting a fixture assembly relative to at least one of the paint robot and the overspray-free paint applicator, the fixture assembly configured to hold an object to be painted by the overspray-free paint applicator, the first fixture robot including a first gripper configured to grab a first portion of the fixture assembly, and the first fixture robot configured to lift and orient the fixture assembly via the first gripper.
Abstract:
An overspray-free paint system includes: a paint robot including an overspray-free paint applicator; and a first fixture robot for lifting and orienting a fixture assembly relative to at least one of the paint robot and the overspray-free paint applicator, the fixture assembly configured to hold an object to be painted by the overspray-free paint applicator, the first fixture robot including a first gripper configured to grab a first portion of the fixture assembly, and the first fixture robot configured to lift and orient the fixture assembly via the first gripper.
Abstract:
Systems and methods for changing end-of-arm tools and methods for manufacturing vehicles are provided. An exemplary end-of-arm tool changing system includes a rotatable tool rack configured to hold at least two end-of-arm tools and configured to move a selected end-of-arm tool from a far location to a near location. The exemplary end-of-arm tool changing system further includes a robot configured to reach the near location for attachment of the selected end-of-arm tool to the robot.