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In the following example, we create a :py:class:`~roboticstoolbox.models.URDF.Panda` robot and one of the fast IK solvers available within the :py:class:`~roboticstoolbox.robot.Robot.Robot` class.
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>>> # Make a goal pose
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>>> Tep = panda.fkine([0, -0.3, 0, -2.2, 0, 2, 0.7854])
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>>> # Solve the IK problem
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>>> panda.ik_lm_chan(Tep)
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>>> panda.ik_LM(Tep)
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In the following example, we create a :py:class:`~roboticstoolbox.models.URDF.Panda` robot and and then get the :py:class:`~roboticstoolbox.robot.ETS.ETS` representation. Subsequently, we use one of the fast IK solvers available within the :py:class:`~roboticstoolbox.robot.ETS.ETS` class.
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@@ -131,7 +127,7 @@ In the following example, we create a :py:class:`~roboticstoolbox.models.URDF.Pa
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>>> # Make a goal pose
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>>> Tep = ets.fkine([0, -0.3, 0, -2.2, 0, 2, 0.7854])
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>>> # Solve the IK problem
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>>> ets.ik_lm_chan(Tep)
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>>> ets.ik_LM(Tep)
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@@ -230,11 +226,10 @@ Additionally, these :py:class:`Class` based solvers have been implemented as met
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