File size: 4,226 Bytes
33c14d6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 | """Reachability check: damped least-squares IK from the home pose to every square and the bin.
Target: gripperframe site at square centre + the selected mesh's grasp height.
This is a kinematic check only, not a collision-free pick-and-place validation.
Reports position error and tilt for each square. Run: .venv/bin/python sim/check_reach.py
"""
from __future__ import annotations
import argparse
import json
from pathlib import Path
import mujoco
import numpy as np
HERE = Path(__file__).resolve().parent
POS_TOL = 0.003
TILT_TOL_DEG = 45.0
APPROACH_TILTS = (0, 15, 30, 40) # degrees forward from vertical
ARM_DOF = 5 # pan, lift, elbow, wrist_flex, wrist_roll
def ik(m, d, site_id, target_pos, target_axis=np.array([0, 0, -1.0]), iters=300, damping=1e-4):
lo, hi = m.jnt_range[:ARM_DOF, 0], m.jnt_range[:ARM_DOF, 1]
jacp = np.zeros((3, m.nv)); jacr = np.zeros((3, m.nv))
for _ in range(iters):
mujoco.mj_forward(m, d)
p = d.site_xpos[site_id]
R = d.site_xmat[site_id].reshape(3, 3)
a = R[:, 0] # gripper axis in world
e_pos = target_pos - p
e_rot = np.cross(a, target_axis) # small-angle rotation aligning a to target
mujoco.mj_jacSite(m, d, jacp, jacr, site_id)
J = np.vstack([jacp[:, :ARM_DOF], 0.3 * jacr[:, :ARM_DOF]])
e = np.concatenate([e_pos, 0.3 * e_rot])
dq = J.T @ np.linalg.solve(J @ J.T + damping * np.eye(6), e)
dq = np.clip(dq, -0.15, 0.15)
d.qpos[:ARM_DOF] = np.clip(d.qpos[:ARM_DOF] + dq, lo, hi)
mujoco.mj_forward(m, d)
p = d.site_xpos[site_id]; a = d.site_xmat[site_id].reshape(3, 3)[:, 0]
tilt = np.degrees(np.arccos(np.clip(a @ target_axis, -1, 1)))
return np.linalg.norm(target_pos - p), tilt, d.qpos[:ARM_DOF].copy()
def main():
pieces = json.loads((HERE / "assets/chess/manifest.json").read_text())["pieces"]
ap = argparse.ArgumentParser(description=__doc__)
ap.add_argument("--piece", choices=pieces, default="pawn")
args = ap.parse_args()
grasp_h = pieces[args.piece]["grasp_z_m"]
m = mujoco.MjModel.from_xml_path(str(HERE / "chess_scene.xml"))
d = mujoco.MjData(m)
home = m.key("home").qpos[:ARM_DOF].copy()
sid = m.site("gripperframe").id
mujoco.mj_forward(m, d)
targets = {}
for f in "abcdefgh":
for r in range(1, 9):
targets[f"{f}{r}"] = m.site(f"sq_{f}{r}").pos + m.body("board").pos + [0, 0, grasp_h]
targets["bin"] = m.body("bin").pos + [0, 0, 0.06]
ok, bad = [], []
grid = {}
for name, t in targets.items():
best = None
# try a vertical approach first, then progressively tilt the gripper forward (toward the human)
for tilt_deg in APPROACH_TILTS:
th = np.radians(tilt_deg)
axis = np.array([np.sin(th), 0.0, -np.cos(th)])
for seed in (home, np.array([0, -0.5, 0.8, 1.2, 0]), np.array([0, 0.3, 0.3, 1.2, 0]), np.array([0, 0.8, -0.3, 1.0, 0])):
d.qpos[:ARM_DOF] = seed
err, tilt, q = ik(m, d, sid, t, target_axis=axis)
tilt_total = np.degrees(np.arccos(np.clip(-d.site_xmat[sid].reshape(3, 3)[2, 0], -1, 1)))
if best is None or err < best[0]:
best = (err, tilt_total, q)
if best[0] < POS_TOL:
break
err, tilt, q = best
good = err < POS_TOL and tilt < TILT_TOL_DEG
(ok if good else bad).append(name)
grid[name] = (err, tilt)
print(f"{args.piece}: grasp height {grasp_h*1000:.2f} mm; kinematic reach only")
print("rank " + " ".join(f" {f} " for f in "abcdefgh") + " (pos err mm / gripper tilt from vertical deg)")
for r in range(8, 0, -1):
row = []
for f in "abcdefgh":
err, tilt = grid[f"{f}{r}"]
mark = " " if f"{f}{r}" in ok else "X"
row.append(f"{err*1000:4.1f}/{tilt:2.0f}{mark}")
print(f" {r} " + " ".join(row))
e, t = grid["bin"]
print(f"bin: {e*1000:.1f} mm / {t:.0f} deg {'ok' if 'bin' in ok else 'X'}")
print(f"\nreachable: {len(ok)}/{len(targets)} unreachable: {bad if bad else 'none'}")
if __name__ == "__main__":
main()
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