Fix nx related work on chokecherry #37
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…h-testbed into feature/wpts_mpc
…nto feature/wpts_mpc
…h-testbed into feature/wpts_mpc
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@harryzhang1018 let's clean this up sooner rather than later
atk.yml
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| @@ -82,7 +86,7 @@ services: | |||
| USER_UID: "@{uid}" | |||
| USER_GID: "@{gid}" | |||
| APT_DEPENDENCIES: "bash zsh vim git git-lfs python3-pip python3-tk python3-opencv rapidjson-dev" | |||
| PIP_REQUIREMENTS: "wa_simulator pandas matplotlib numpy>=1.19 opencv-python tornado black Pillow torch torchvision pyserial nvidia-pyindex" | |||
| PIP_REQUIREMENTS: "wa_simulator pandas matplotlib numpy>=1.19 opencv-python tornado black Pillow torch torchvision pyserial nvidia-pyindex casadi cvxpy scipy osqp" | |||
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do we still need these?
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Yes, "casadi cvxpy scipy osqp" is for MPC, I also need to add pip and apt dependencies for RTK/GPS driver to run
| @@ -281,6 +281,10 @@ def LabelConeAssets(): | |||
| vehicle.SetTireType(tire_model) | |||
| vehicle.SetInitPosition(chrono.ChCoordsysD(initLoc, initRot)) | |||
| vehicle.SetTireStepSize(tire_step_size) | |||
| vehicle.SetMaxMotorVoltageRatio(0.16) | |||
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needed? is this only in chrono-internal?
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I don't think this needed to be merged into main cuz we are not gonna run simulation on Jetson right?
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@harryzhang1018 your job is to figure out what we need here (if anything)
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Pretty much all of the keras files can be deleted... We have a seperate repo (which should end up somewhere on SBEL github) for training, and it takes <20 min to train each model.
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Might just be nice to have at least one either on the github or loaded (similar to Yolo)... but that should come from a control node PR not from here
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| def mpc_cvxpy_solver_v2(xref,yref,v_current,u_current): |
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Keep? if yes, please add docstrings
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can we just create a data folder somewhere that has all these paths?
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This also doesn't need to be merged, part of Path Planning PR
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| self.go = False | ||
| self.error_state = VehicleState() | ||
| self.file = open("/home/art-ishaan/art-ishaan/workspace/src/path_planning/path_planning/lot17_sinsquare_sv.csv") |
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let's not use hardcoded paths
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i'd recommend cloning locally and deleting stuff you don't need and then pushing back to this branch. Do we need all these datafiles? Can we have a datafolder on box or something that houses all of them? |
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@AaronYoung5 @StefanCaldararu |
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@harryzhang1018 Looked through this. IMO, best way to go about things is as follows:
- start by making sure everything that we want to keep is backed up. From what I can tell, these are path files and keras files. (I think you've already done this). I think it's fine to have these backed up externally for now, until we find a home for them (we should really take care of Imitation Learning ML training needs to be added somewhere #39).
- Test the real vehicle with the new changes Aaron has made, and try and get that working.
- Delete this branch/pr once nothing is needed anymore.
Don't merge into master branch