University Technology Corporation

Western Atlas Inc.

Daniel David Frey

Timothy W Hykes

Lawrence Evan Carlson

Eric Stewart Brown

Kevin N Otto

A voluntary closing prosthetic prehensor includes a locking mechanism which may be locked into any position, and released with a small amount of force. With locking enabled, the prehensor opens and closes normally until the user applies sufficient tension to the prehensor cable after the prehensor has closed upon an object. Then, a lever arm attached to the cable rotates, pulling a second cable which causes an elliptical cam to rotate such that its wider portion presses against a pawl, causing the pawl to rotate into engagement with a toothed sector, locking the prehensor closed. When the user releases the force on the cable, the lever arm is biased to return to its normal position, but the prehensor stays closed because the pawl remains engaged with the sector. The cam includes a ratcheting drum which takes up the slack in the second cable. To release the prehensor, the user applies a small amount of force to the first cable, moving the lever arm and pulling the second cable, which rotates the cam. As it starts to rotate, the cam moves away from the pawl, allowing it to rotate away from the sector. The pawl has two links joined at a pivot. The link engaged with the toothed sector pivots to allow the pawl to rotate away from the sector, pulling the engaged link free. The pawl is biased to retract away from the sector, unlocking the prehensor.

Locking mechanism for voluntary closing prosthetic prehensor

A method is provided for virtual machining which helps predict the accuracy of parts to be made on machine tools, allocates errors in design and manufacture of machine tools, and diagnoses the source of errors in machine tools. More particularly, the present invention relates to a method which calculates the 'error shape' of a part being manufactured based upon the position, orientation, velocity and shape of the machine tool. The method predicts the statistical distribution of part size, form, and profile errors in a population of parts by superposing 'error shapes.' The machine errors are diagnosed by matching post process gauging data with a linear combination of 'error shapes.' The method predicts the magnitude and pattern of errors in a machined part, performs a simulation taking into account the geometry of the machine, the commanded machine motions as a function of time, error motions of the machine's components as a function of time, and the shape of the tool. The output is the location of a set of discrete points on the surface of a part.

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Cambridge, MA, United States of America

Daniel David Frey