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multi-timestep collision avoidance and storing the value function at every timestep
buinm
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Sep 14, 2021
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buinm
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buinm
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Hey Ken,
Thank you for making the changes, these changes will be very useful for us going forward. There are just some comments over some of your changes, please let have a look at them and let me know if there are anything concerning you.
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| # saving value function at each timestep | ||
| if grid.dims == 3: |
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It might be shorter to do the following:
valfuns = np.zeros(np.insert(tuple(grid.pts_each_dim), grid.dims, len(tau)))
valfuns[..., -1 ] = V_0.asnumpy()
| if "TargetSetMode" in compMethod: | ||
| if compMethod["TargetSetMode"] == "max": | ||
| tmp_val = np.maximum(V_0.asnumpy(), constraint) | ||
| tmp_val = np.maximum(V_0.asnumpy(), -constraint_i) |
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I think it's better to keep it as constraint. The negate operation on the constraint value array should just be done by users before passing in the variables to HJSolver function call
| t_minh= hcl.asarray(np.array((tNow, tau[i]))) | ||
| # taking obstacle at each timestep | ||
| if "TargetSetMode" in compMethod and constraint_dim > grid.dims: | ||
| constraint_i = constraint[...,i] |
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Is it a bit too many indentations for the constraint_i = constraint[...,i]
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multi-timestep collision avoidance and storing the value function at every timestep