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fix(ik): unify ik_XX/ikine_XX return types and fix IK docs #652

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Merged
petercorke merged 7 commits into from
Aug 26, 2026
Merged

fix(ik): unify ik_XX/ikine_XX return types and fix IK docs #652

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b0d2448
fix(ik): add IKSolution.__getitem__/__repr__, fix docstring typos
petercorke Aug 26, 2026
edf102f
fix(ik): unify ik_LM/ik_NR/ik_GN's return type with IKSolution
petercorke Aug 26, 2026
96411e7
fix(dhrobot): remove 5 completely broken dead IK methods
petercorke Aug 26, 2026
fc5ca49
fix(examples): repair ik_exp.py to use the real ik_NR/ik_GN/ik_LM API
petercorke Aug 26, 2026
d9d4603
docs: fix Levenberg-Marquardt spelling in IK docs
petercorke Aug 26, 2026
c3449bb
test(ik): add regression tests for IKSolution/ik_XX return-type changes
petercorke Aug 26, 2026
6d85262
Merge origin/main (PRs #648-#650 and others) to resolve conflicts and…
petercorke Aug 26, 2026
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4 changes: 2 additions & 2 deletions docs/source/IK/ik_lm.rst
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Original file line number Diff line number Diff line change
@@ -1,5 +1,5 @@
IK_LM - Levemberg-Marquadt Numerical IK
---------------------------------------
IK_LM - Levenberg-Marquardt Numerical IK
----------------------------------------

.. currentmodule:: roboticstoolbox.robot.IK

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2 changes: 1 addition & 1 deletion docs/source/intro.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -103,7 +103,7 @@ All robots can generate a random joint configuration informed by joint limits, i
>>> puma.random_q()

``ikine_LM`` is a generalised iterative numerical solution based on
Levenberg-Marquadt minimization, and additional status results are also
Levenberg-Marquardt minimization, and additional status results are also
returned as part of a named tuple.

.. warning::
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160 changes: 30 additions & 130 deletions examples/ik_exp.py
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Original file line number Diff line number Diff line change
@@ -1,17 +1,7 @@
import numpy as np
import roboticstoolbox as rtb
import spatialmath as sm
import fknm
import time
import swift
import spatialgeometry as sg
import sys
from ansitable import ANSITable

from numpy import ndarray
from spatialmath import SE3
from typing import Union, overload, List, Set

# Our robot and ETS
robot = rtb.models.Panda()
ets = robot.ets()
Expand Down Expand Up @@ -42,7 +32,7 @@
tol = 1e-6

# Reject solutions with invalid joint limits
reject_jl = True
joint_limits = True


class IK:
Expand All @@ -64,164 +54,74 @@ def __init__(self, name, solve, problems=problems):


solvers = [
# IK(
# "Newton Raphson",
# lambda Tep: ets.ik_nr(
# Tep,
# q0=None,
# ilimit=ilimit,
# slimit=slimit,
# tol=tol,
# reject_jl=reject_jl,
# we=we,
# use_pinv=False,
# pinv_damping=0.0,
# ),
# ),
# IK(
# "Gauss Newton",
# lambda Tep: ets.ik_gn(
# Tep,
# q0=None,
# ilimit=ilimit,
# slimit=slimit,
# tol=tol,
# reject_jl=reject_jl,
# we=we,
# use_pinv=False,
# pinv_damping=0.0,
# ),
# ),
IK(
"Newton Raphson Pinv",
lambda Tep: ets.ik_nr(
lambda Tep: ets.ik_NR(
Tep,
q0=None,
ilimit=ilimit,
slimit=slimit,
tol=tol,
reject_jl=reject_jl,
we=we,
use_pinv=True,
joint_limits=joint_limits,
mask=we,
pinv=True,
pinv_damping=0.0,
),
),
IK(
"Gauss Newton Pinv",
lambda Tep: ets.ik_gn(
lambda Tep: ets.ik_GN(
Tep,
q0=None,
ilimit=ilimit,
slimit=slimit,
tol=tol,
reject_jl=reject_jl,
we=we,
use_pinv=True,
joint_limits=joint_limits,
mask=we,
pinv=True,
pinv_damping=0.0,
),
),
IK(
"LM Chan 0.1",
lambda Tep: ets.ik_lm_chan(
lambda Tep: ets.ik_LM(
Tep,
q0=None,
ilimit=ilimit,
slimit=slimit,
tol=tol,
reject_jl=reject_jl,
we=we,
λ=0.1,
joint_limits=joint_limits,
mask=we,
k=0.1,
method="chan",
),
),
# IK(
# "LM Chan 1.0",
# lambda Tep: ets.ik_lm_chan(
# Tep,
# q0=None,
# ilimit=ilimit,
# slimit=slimit,
# tol=tol,
# reject_jl=reject_jl,
# we=we,
# λ=1.0,
# ),
# ),
# IK(
# "LM Wampler",
# lambda Tep: ets.ik_lm_wampler(
# Tep,
# q0=None,
# ilimit=ilimit,
# slimit=slimit,
# tol=tol,
# reject_jl=reject_jl,
# we=we,
# λ=1e-2,
# ),
# ),
IK(
"LM Wampler 1e-4",
lambda Tep: ets.ik_lm_wampler(
lambda Tep: ets.ik_LM(
Tep,
q0=None,
ilimit=ilimit,
slimit=slimit,
tol=tol,
reject_jl=reject_jl,
we=we,
λ=1e-4,
joint_limits=joint_limits,
mask=we,
k=1e-4,
method="wampler",
),
),
# IK(
# "LM Wampler 1e-6",
# lambda Tep: ets.ik_lm_wampler(
# Tep,
# q0=None,
# ilimit=ilimit,
# slimit=slimit,
# tol=tol,
# reject_jl=reject_jl,
# we=we,
# λ=1e-6,
# ),
# ),
# IK(
# "LM Sugihara 0.001",
# lambda Tep: ets.ik_lm_sugihara(
# Tep,
# q0=None,
# ilimit=ilimit,
# slimit=slimit,
# tol=tol,
# reject_jl=reject_jl,
# we=we,
# λ=0.001,
# ),
# ),
# IK(
# "LM Sugihara 0.01",
# lambda Tep: ets.ik_lm_sugihara(
# Tep,
# q0=None,
# ilimit=ilimit,
# slimit=slimit,
# tol=tol,
# reject_jl=reject_jl,
# we=we,
# λ=0.01,
# ),
# ),
IK(
"LM Sugihara 0.1",
lambda Tep: ets.ik_lm_sugihara(
lambda Tep: ets.ik_LM(
Tep,
q0=None,
ilimit=ilimit,
slimit=slimit,
tol=tol,
reject_jl=reject_jl,
we=we,
λ=0.1,
joint_limits=joint_limits,
mask=we,
k=0.1,
method="sugihara",
),
),
]
Expand All @@ -230,13 +130,13 @@ def __init__(self, name, solve, problems=problems):
print(i + 1)

for solver in solvers:
_, success, iterations, searches, residual = solver.solve(Tep[i])
sol = solver.solve(Tep[i])

if success:
solver.success[i] = success
solver.iterations[i] = iterations
solver.searches[i] = searches
solver.residual[i] = residual
if sol.success:
solver.success[i] = sol.success
solver.iterations[i] = sol.iterations
solver.searches[i] = sol.searches
solver.residual[i] = sol.residual
solver.total_iterations += solver.iterations[i]
solver.total_searches += solver.searches[i]
else:
Expand Down
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