constrained planning, robot segmentation
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@@ -121,7 +121,7 @@ def get_stomp_cov_jit(
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else:
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A[k * horizon + i, k * horizon + index] = fd_array[j + 3]
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R = torch.matmul(A.transpose(-2, -1), A)
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R = torch.matmul(A.transpose(-2, -1).clone(), A.clone())
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M = torch.inverse(R)
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scaled_M = (1 / horizon) * M / (torch.max(torch.abs(M), dim=1)[0].unsqueeze(0))
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cov = M / torch.max(torch.abs(M))
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@@ -132,7 +132,6 @@ def get_stomp_cov_jit(
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scale_tril = torch.linalg.cholesky(cov)
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else:
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scale_tril = cov
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"""
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k = 0
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act_cov_matrix = cov[k * horizon:k * horizon + horizon, k * horizon:k * horizon + horizon]
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