yxyang / fast_and_efficient Goto Github PK

Hi, Thanks for releasing this codebase!

This runs great on the A1 but we're having some issues getting this work on our Go1.
Have you by any chance also tried running this on the Go1 or do you have any idea what we'd have to adjust to make it work?

Thanks in advance,
Simon

Hello,
After completing the three setup steps, and also I copied robot_interface.XXX.so file to the main directory. Then, tried to run script convex_mpc_controller_example.py, an error "No module named 'robot_interface" appears. Is there way to fix this issue
Thanks!

Hello,

After following the setup instructions without errors, I got an error while running "convex_mpc_controller_example.py" about the type of the argument provided to the "compute_contact_forces" function, but I didn't changed anything in the code!
I've just run this command (provided in your repo) : python -m src.convex_mpc_controller.convex_mpc_controller_example --show_gui=True --max_time_secs=10 --world=plane from the main folder.

pybullet build time: May 20 2022 19:44:17
argv[0]=
startThreads creating 1 threads.
starting thread 0
started thread 0
argc=3
argv[0] = --unused
argv[1] =
argv[2] = --start_demo_name=Physics Server
ExampleBrowserThreadFunc started
X11 functions dynamically loaded using dlopen/dlsym OK!
X11 functions dynamically loaded using dlopen/dlsym OK!
Creating context
Created GL 3.3 context
Direct GLX rendering context obtained
Making context current
GL_VENDOR=NVIDIA Corporation
GL_RENDERER=NVIDIA GeForce GT 1030/PCIe/SSE2
GL_VERSION=3.3.0 NVIDIA 525.78.01
GL_SHADING_LANGUAGE_VERSION=3.30 NVIDIA via Cg compiler
pthread_getconcurrency()=0
Version = 3.3.0 NVIDIA 525.78.01
Vendor = NVIDIA Corporation
Renderer = NVIDIA GeForce GT 1030/PCIe/SSE2
b3Printf: Selected demo: Physics Server
startThreads creating 1 threads.
starting thread 0
started thread 0
MotionThreadFunc thread started
ven = NVIDIA Corporation
ven = NVIDIA Corporation
I0405 09:33:06.039097 140688990267200 locomotion_controller.py:294] Switched to Crawling gait.
I0405 09:33:06.039403 140688627767040 locomotion_controller.py:310] Low level thread started...
I0405 09:33:06.039460 140688627767040 locomotion_controller.py:248] Standing up.
I0405 09:33:06.338073 140688627767040 locomotion_controller.py:297] Switched to Trotting gait.
/home/smonnet/Desktop/quadruped-sim-master/fast_and_efficient/src/convex_mpc_controller/com_velocity_estimator.py:52: FutureWarning: rcond parameter will change to the default of machine precision times max(M, N) where M and N are the input matrix dimensions.
To use the future default and silence this warning we advise to pass rcond=None, to keep using the old, explicitly pass rcond=-1.
normal_vec = np.linalg.lstsq(contact_foot_positions, np.ones(4))[0]
I0405 09:33:06.341569 140688627767040 locomotion_controller.py:251] Walking.
Exception in thread Thread-1:
Traceback (most recent call last):
File "/usr/lib/python3.8/threading.py", line 932, in _bootstrap_inner
self.run()
File "/usr/lib/python3.8/threading.py", line 870, in run
self._target(*self._args, **self._kwargs)
File "/home/smonnet/Desktop/quadruped-sim-master/fast_and_efficient/src/convex_mpc_controller/locomotion_controller.py", line 322, in run
action, qp_sol = self.get_action()
File "/home/smonnet/Desktop/quadruped-sim-master/fast_and_efficient/src/convex_mpc_controller/locomotion_controller.py", line 211, in get_action
stance_action, qp_sol = self._stance_controller.get_action()
File "/home/smonnet/Desktop/quadruped-sim-master/fast_and_efficient/src/convex_mpc_controller/torque_stance_leg_controller_mpc.py", line 174, in get_action
predicted_contact_forces = self._cpp_mpc.compute_contact_forces(
TypeError: compute_contact_forces(): incompatible function arguments. The following argument types are supported:
1. (self: mpc_osqp.ConvexMpc, arg0: List[float], arg1: List[float], arg2: List[float], arg3: List[float], arg4: List[int], arg5: List[float], arg6: List[float], arg7: List[float], arg8: List[float], arg9: List[float], arg10: List[float]) -> List[float]

Invoked with: <mpc_osqp.ConvexMpc object at 0x7ff4a92335f0>, array([0. , 0. , 0.23861794]), array([ 4.42300643e-06, -1.66188485e-08, 1.05292600e-06]), array([-0.00122399, -0.01933636, 0. ]), array([-4.02889509e-06, 2.06527659e-07, 1.00000000e+00]), [0, 0, 0], array([0., 1., 1., 0., 0., 1., 1., 0., 0., 1., 1., 0., 0., 1., 1., 0., 0.,
1., 1., 0., 0., 1., 1., 0., 0., 1., 1., 0., 0., 1., 1., 0., 0., 1.,
1., 0., 0., 1., 1., 0.]), array([ 0.17128076, -0.13418603, -0.2422553 , 0.1719579 , 0.12992437,
-0.24194507, -0.1778831 , -0.13415863, -0.23550281, -0.17788233,
0.12993178, -0.23517963]), array([0.6, 0.6, 0.6, 0.6]), array([0. , 0. , 0.3]), array([0.09, 0. , 0. ]), array([0., 0., 0.]), array([0., 0., 0.])

I would really appreciate if you have any idea about the reason why I get this error ! I'm using Python 3.8.10 and Ubuntu 20.04.

Thanks a lot,
Stephen

Hi, thank you for the great work and I really appreciate it! I was trying to replicate some results in the paper but encountered some troubles on the real robot.

After the robot stands up, I press L2 + B to transition it into the damping mode. It soon loses forces and subsequently lays down. Reviewing the code in whole_body_controller_example.py, I find there's a reset process for A1Robot initialization, which tries to position the robot under the standing pose. Notably, this process utilizes Motor Position Control Mode for implementation. However, it seems the pure position control mode alone cannot bring the robot to its desired poses without added torques. A related discussion on a similar problem can be found in the Unitree official repository at: unitreerobotics/unitree_legged_sdk#111.

Thus I'm curious whether the code enables the robot to stand up under the pure position control mode?