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- /**
- * Marlin 3D Printer Firmware
- * Copyright (c) 2020 MarlinFirmware [https://github.com/MarlinFirmware/Marlin]
- *
- * Based on Sprinter and grbl.
- * Copyright (c) 2011 Camiel Gubbels / Erik van der Zalm
- *
- * This program is free software: you can redistribute it and/or modify
- * it under the terms of the GNU General Public License as published by
- * the Free Software Foundation, either version 3 of the License, or
- * (at your option) any later version.
- *
- * This program is distributed in the hope that it will be useful,
- * but WITHOUT ANY WARRANTY; without even the implied warranty of
- * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- * GNU General Public License for more details.
- *
- * You should have received a copy of the GNU General Public License
- * along with this program. If not, see <https://www.gnu.org/licenses/>.
- *
- */
-
- /**
- * planner_bezier.cpp
- *
- * Compute and buffer movement commands for bezier curves
- */
-
- #include "../inc/MarlinConfig.h"
-
- #if ENABLED(BEZIER_CURVE_SUPPORT)
-
- #include "planner.h"
- #include "motion.h"
- #include "temperature.h"
-
- #include "../MarlinCore.h"
- #include "../gcode/queue.h"
-
- // See the meaning in the documentation of cubic_b_spline().
- #define MIN_STEP 0.002f
- #define MAX_STEP 0.1f
- #define SIGMA 0.1f
-
- // Compute the linear interpolation between two real numbers.
- static inline float interp(const_float_t a, const_float_t b, const_float_t t) { return (1 - t) * a + t * b; }
-
- /**
- * Compute a Bézier curve using the De Casteljau's algorithm (see
- * https://en.wikipedia.org/wiki/De_Casteljau%27s_algorithm), which is
- * easy to code and has good numerical stability (very important,
- * since Arudino works with limited precision real numbers).
- */
- static inline float eval_bezier(const_float_t a, const_float_t b, const_float_t c, const_float_t d, const_float_t t) {
- const float iab = interp(a, b, t),
- ibc = interp(b, c, t),
- icd = interp(c, d, t),
- iabc = interp(iab, ibc, t),
- ibcd = interp(ibc, icd, t);
- return interp(iabc, ibcd, t);
- }
-
- /**
- * We approximate Euclidean distance with the sum of the coordinates
- * offset (so-called "norm 1"), which is quicker to compute.
- */
- static inline float dist1(const_float_t x1, const_float_t y1, const_float_t x2, const_float_t y2) { return ABS(x1 - x2) + ABS(y1 - y2); }
-
- /**
- * The algorithm for computing the step is loosely based on the one in Kig
- * (See https://sources.debian.net/src/kig/4:15.08.3-1/misc/kigpainter.cpp/#L759)
- * However, we do not use the stack.
- *
- * The algorithm goes as it follows: the parameters t runs from 0.0 to
- * 1.0 describing the curve, which is evaluated by eval_bezier(). At
- * each iteration we have to choose a step, i.e., the increment of the
- * t variable. By default the step of the previous iteration is taken,
- * and then it is enlarged or reduced depending on how straight the
- * curve locally is. The step is always clamped between MIN_STEP/2 and
- * 2*MAX_STEP. MAX_STEP is taken at the first iteration.
- *
- * For some t, the step value is considered acceptable if the curve in
- * the interval [t, t+step] is sufficiently straight, i.e.,
- * sufficiently close to linear interpolation. In practice the
- * following test is performed: the distance between eval_bezier(...,
- * t+step/2) is evaluated and compared with 0.5*(eval_bezier(...,
- * t)+eval_bezier(..., t+step)). If it is smaller than SIGMA, then the
- * step value is considered acceptable, otherwise it is not. The code
- * seeks to find the larger step value which is considered acceptable.
- *
- * At every iteration the recorded step value is considered and then
- * iteratively halved until it becomes acceptable. If it was already
- * acceptable in the beginning (i.e., no halving were done), then
- * maybe it was necessary to enlarge it; then it is iteratively
- * doubled while it remains acceptable. The last acceptable value
- * found is taken, provided that it is between MIN_STEP and MAX_STEP
- * and does not bring t over 1.0.
- *
- * Caveat: this algorithm is not perfect, since it can happen that a
- * step is considered acceptable even when the curve is not linear at
- * all in the interval [t, t+step] (but its mid point coincides "by
- * chance" with the midpoint according to the parametrization). This
- * kind of glitches can be eliminated with proper first derivative
- * estimates; however, given the improbability of such configurations,
- * the mitigation offered by MIN_STEP and the small computational
- * power available on Arduino, I think it is not wise to implement it.
- */
- void cubic_b_spline(
- const xyze_pos_t &position, // current position
- const xyze_pos_t &target, // target position
- const xy_pos_t (&offsets)[2], // a pair of offsets
- const_feedRate_t scaled_fr_mm_s, // mm/s scaled by feedrate %
- const uint8_t extruder
- ) {
- // Absolute first and second control points are recovered.
- const xy_pos_t first = position + offsets[0], second = target + offsets[1];
-
- xyze_pos_t bez_target;
- bez_target.set(position.x, position.y);
- float step = MAX_STEP;
-
- millis_t next_idle_ms = millis() + 200UL;
-
- for (float t = 0; t < 1;) {
-
- thermalManager.manage_heater();
- millis_t now = millis();
- if (ELAPSED(now, next_idle_ms)) {
- next_idle_ms = now + 200UL;
- idle();
- }
-
- // First try to reduce the step in order to make it sufficiently
- // close to a linear interpolation.
- bool did_reduce = false;
- float new_t = t + step;
- NOMORE(new_t, 1);
- float new_pos0 = eval_bezier(position.x, first.x, second.x, target.x, new_t),
- new_pos1 = eval_bezier(position.y, first.y, second.y, target.y, new_t);
- for (;;) {
- if (new_t - t < (MIN_STEP)) break;
- const float candidate_t = 0.5f * (t + new_t),
- candidate_pos0 = eval_bezier(position.x, first.x, second.x, target.x, candidate_t),
- candidate_pos1 = eval_bezier(position.y, first.y, second.y, target.y, candidate_t),
- interp_pos0 = 0.5f * (bez_target.x + new_pos0),
- interp_pos1 = 0.5f * (bez_target.y + new_pos1);
- if (dist1(candidate_pos0, candidate_pos1, interp_pos0, interp_pos1) <= (SIGMA)) break;
- new_t = candidate_t;
- new_pos0 = candidate_pos0;
- new_pos1 = candidate_pos1;
- did_reduce = true;
- }
-
- // If we did not reduce the step, maybe we should enlarge it.
- if (!did_reduce) for (;;) {
- if (new_t - t > MAX_STEP) break;
- const float candidate_t = t + 2 * (new_t - t);
- if (candidate_t >= 1) break;
- const float candidate_pos0 = eval_bezier(position.x, first.x, second.x, target.x, candidate_t),
- candidate_pos1 = eval_bezier(position.y, first.y, second.y, target.y, candidate_t),
- interp_pos0 = 0.5f * (bez_target.x + candidate_pos0),
- interp_pos1 = 0.5f * (bez_target.y + candidate_pos1);
- if (dist1(new_pos0, new_pos1, interp_pos0, interp_pos1) > (SIGMA)) break;
- new_t = candidate_t;
- new_pos0 = candidate_pos0;
- new_pos1 = candidate_pos1;
- }
-
- // Check some postcondition; they are disabled in the actual
- // Marlin build, but if you test the same code on a computer you
- // may want to check they are respect.
- /*
- assert(new_t <= 1.0);
- if (new_t < 1.0) {
- assert(new_t - t >= (MIN_STEP) / 2.0);
- assert(new_t - t <= (MAX_STEP) * 2.0);
- }
- */
-
- step = new_t - t;
- t = new_t;
-
- // Compute and send new position
- xyze_pos_t new_bez = LOGICAL_AXIS_ARRAY(
- interp(position.e, target.e, t), // FIXME. Wrong, since t is not linear in the distance.
- new_pos0,
- new_pos1,
- interp(position.z, target.z, t), // FIXME. Wrong, since t is not linear in the distance.
- interp(position.i, target.i, t), // FIXME. Wrong, since t is not linear in the distance.
- interp(position.j, target.j, t), // FIXME. Wrong, since t is not linear in the distance.
- interp(position.k, target.k, t) // FIXME. Wrong, since t is not linear in the distance.
- );
- apply_motion_limits(new_bez);
- bez_target = new_bez;
-
- #if HAS_LEVELING && !PLANNER_LEVELING
- xyze_pos_t pos = bez_target;
- planner.apply_leveling(pos);
- #else
- const xyze_pos_t &pos = bez_target;
- #endif
-
- if (!planner.buffer_line(pos, scaled_fr_mm_s, active_extruder, step))
- break;
- }
- }
-
- #endif // BEZIER_CURVE_SUPPORT
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