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I've noticed that the return value for b2GearJoint::SolvePositionConstraints of return linearError < b2_linearSlop is commented with TODO_ERIN not implemented and that the linearError variable is only initialized to 0.0f making the function always return true.
Might something like the following be an algorithmic description of an implementation for this that would be reasonable/desirable/helpful?
Set a linear error variable to the max magnitude of the linear position deltas (of m_mA * impulse * JvA, m_mB * impulse * JvBD, etc.).
Set a angular error variable to the max angular position delta (of aA += m_iA * impulse * JwA, aB += m_iB * impulse * JwB, etc.).
Return true if the linear error is less than b2_linearSlop and the angular error is less than b2_angularSlop, or return false otherwise.
With potentially an optimization like using the magnitude squared instead of the magnitude to avoid doing the square roots and compensating with using the squared value of b2_linearSlop.
The text was updated successfully, but these errors were encountered:
I've noticed that the return value for
b2GearJoint::SolvePositionConstraints
ofreturn linearError < b2_linearSlop
is commented withTODO_ERIN not implemented
and that thelinearError
variable is only initialized to0.0f
making the function always return true.Might something like the following be an algorithmic description of an implementation for this that would be reasonable/desirable/helpful?
m_mA * impulse * JvA
,m_mB * impulse * JvBD
, etc.).aA += m_iA * impulse * JwA
,aB += m_iB * impulse * JwB
, etc.).b2_linearSlop
and the angular error is less thanb2_angularSlop
, or return false otherwise.With potentially an optimization like using the magnitude squared instead of the magnitude to avoid doing the square roots and compensating with using the squared value of
b2_linearSlop
.The text was updated successfully, but these errors were encountered: