@@ -4,8 +4,7 @@ The <a href="https://github.com/projectchrono/chrono">Chrono</a> library is the
44to simulate robots and create environments for reinforcement learning agents. As such, knowing your way around
55Chrono is essential. However, Chrono is a relatively large library with many components and therefore not necessarily easy
66to grasp. In a series of examples, we will see main components of the library that _ bitrl_ utilizes.
7-
8- You should have compiled Chrono with <a href =" https://irrlicht.sourceforge.io/ " >Irrlicht</a > support.
7+ Note that you should have compiled Chrono with <a href =" https://irrlicht.sourceforge.io/ " >Irrlicht</a > support in order to be able to run this example.
98
109The main interface for creating rigid bodies in Chrono is the <a href =" https://api.projectchrono.org/9.0.0/classchrono_1_1_ch_body.html " >ChBody</a >
1110class. You can also find this <a href =" https://api.projectchrono.org/9.0.0/rigid_bodies.html " > Rigid Bodies</a > helpful.
159158T = (R, p)
160159$$
161160
162- where $R $ is a rotation matrix and $p $ is a translation vector. Chrono uses quaternions to express rotations but
161+ where \f$R\f $ is a rotation matrix and \f$p\f $ is a translation vector. Chrono uses quaternions to express rotations but
163162let's keep the discussion simple. Then
164163
165164@code
166165ref_frame = ( R_wr , p_wr )
167166child_frame_in_ref = ( R_rc , p_rc )
168167@endcode
169168
170- where $p_ {wr} = (0,0,0)$, $p_ {rc}=(0, 0, 0.22)$. When we multiply the two frames we do something equivalent to
169+ where \f $p_ {wr} = (0,0,0)\f $, \f $p_ {rc}=(0, 0, 0.22)\f $. When we multiply the two frames we do something equivalent to
171170
172171@code
173172(R_wr, p_wr) * (R_rc, p_rc) = ( R_wr * R_rc , p_wr + R_wr p_rc )
174173@endcode
175174
176- However, the two frames are not rotated so both $R_ {wr}$ and $R_ {rc}$ are actually the identity matrix. Thus, we end up with
175+ However, the two frames are not rotated so both \f $R_ {wr}\f $ and \f $R_ {rc}\f $ are actually the identity matrix. Thus, we end up with
177176
178177$$
179178p_{wr} + R_{wr} p_{rc} = (0, 0, 0.22)
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