I wrote a message about this some time ago, but its contents are still essentially accurate: http://mid.gmane.org/20081022160842.ga6...@unpythonic.net
When converting complex curves like nurbs into gcode, the relevant behavior of the motion planner is this: | Make sure moves are "long enough" | --------------------------------- | Principally because of the rule that "the machine will never move at | such a speed that it cannot come to a complete stop at the end of the | current movement", there is a minimum movement length that will allow | the machine to keep up a requested feed rate with a given acceleration | setting. | | The acceleration and deceleration phase each use half the inifile | MAX_ACCELERATION. In a blend that is an exact reversal, this causes the | total axis acceleration to equal the inifile MAX_ACCELERATION. In other | cases, the actual machine acceleration is somewhat less than the inifile | acceleration | | To keep up feed rate, the move must be longer than the distance it takes | to accelerate from 0 to the desired feed rate and then stop again. | Using A as 1/2 the inifile MAX_ACCELERATION and F as the feed rate | *in units per second*, the acceleration time is | ta = F/A | and the acceleration distance is | da = (1/2) * F * ta | the deceleration time and distance are the same, making the critical | distance | d = da + dd = 2*da = F^2 / A. | | For example, for a feed rate of 1 inch per second and an acceleration of | 10 inch/sec^2, the critical distance is 1^2 / 10 = .1 inch. For a feed | rate of .5 inch per second, the critical distance is .5^2 / 10 = .025 | inch. If your curves lie in a plane, consider approximating them with arcs instead of with straight segments. This can give a better approximation with a smaller number of segments, making the typical segment longer. http://emergent.unpy.net/01171767993 - a blog entry of mine on biarcs http://emergent.unpy.net/files/papers/V1Nos1to4_22.pdf - the paper I got the math from (fig1 and associated formulae) I chose "r=1" to give more-equal arcs, rather than following their method for choosing optimal r Jeff ------------------------------------------------------------------------------ Download Intel® Parallel Studio Eval Try the new software tools for yourself. Speed compiling, find bugs proactively, and fine-tune applications for parallel performance. See why Intel Parallel Studio got high marks during beta. http://p.sf.net/sfu/intel-sw-dev _______________________________________________ Emc-users mailing list Emc-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/emc-users