Closed JadBatmobile closed 6 years ago
It is not specific to the constant time implementation btw, the same line in kinematics.py takes 0.28 seconds
In both examples the number of discretization point is 1001, which is really high. You should try 101 points instead as shown below:
instance = algo.TOPPRA([pc_vel, pc_acc], path, gridpoints=np.linspace(0, 1, 101),
solver_wrapper='hotqpoases')
For an even faster speed you can try the newly implemented Seidel's solver as follow
instance = algo.TOPPRA([pc_vel, pc_acc], path, gridpoints=np.linspace(0, 1, 101),
solver_wrapper='seidel')
It should be around 5-10 times faster now. But be aware this implementation is currently quite buggy.
In my PC, the timings are respectively 0.031274843216 secs (101 points/hotqpoases) and 0.0196042060852 secs (101 points/seidel) respectively.
Hello again,
I am running your kinematics_duration.py script, but unfortunately the jnt_traj, aux_traj = instance.compute_trajectory(0, 0) function is taking approximately 0.3 seconds to execute. This seems much longer than the original TOPP implementation, which clocked at around 0.08-0.1 seconds.
What do you think?