Commit 35c5f2e6 authored by Justin Carpentier's avatar Justin Carpentier Committed by GitHub
Browse files

Merge pull request #369 from proyan/devel

[Minor][Spelling] biais in english is bias.
parents 3e4be202 e24897a8
......@@ -84,7 +84,7 @@ class RobotWrapper(object):
def mass(self, q):
return se3.crba(self.model, self.data, q)
def biais(self, q, v):
def bias(self, q, v):
return se3.nle(self.model, self.data, q, v)
def gravity(self, q):
......
......@@ -177,7 +177,7 @@ python shortcuts, also available in RomeoWrapper:
+The size of the robot configuration is given by nq.
+The dimension of its tangent space (velocity) is nv.
+The index of a joint in the tree can be accessed from its name by index (see above).
+The classical algorithms are also binded: com, Jcom, mass, biais, joint gravity, position and velocity of each joint.
+The classical algorithms are also binded: com, Jcom, mass, bias, joint gravity, position and velocity of each joint.
+Shortcuts are also implemented for the placement and the Jacobian (6D, expressed in the body frame) of
the right wrist(rh), left wrist(lh), right ankle(rf), left ankle (lf).For example, you can access the right wrist
placement and Jacobian with robot.Mrh(q) and robot.Jrh(q)
......
......@@ -59,7 +59,7 @@ namespace se3
const container::aligned_vector<Force> & fext);
///
/// \brief Computes the non-linear effects (Corriolis, centrifual and gravitationnal effects), also called the biais terms \f$ b(q,\dot{q}) \f$ of the Lagrangian dynamics:
/// \brief Computes the non-linear effects (Corriolis, centrifual and gravitationnal effects), also called the bias terms \f$ b(q,\dot{q}) \f$ of the Lagrangian dynamics:
/// <CENTER> \f$ \begin{eqnarray} M \ddot{q} + b(q, \dot{q}) = \tau \end{eqnarray} \f$ </CENTER> <BR>
/// \note This function is equivalent to se3::rnea(model, data, q, v, 0).
///
......@@ -68,7 +68,7 @@ namespace se3
/// \param[in] q The joint configuration vector (dim model.nq).
/// \param[in] v The joint velocity vector (dim model.nv).
///
/// \return The biais terms stored in data.nle.
/// \return The bias terms stored in data.nle.
///
inline const Eigen::VectorXd &
nonLinearEffects(const Model & model, Data & data,
......
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