Multidimensional Dynamic Time Warping Implementation in Python - confirm?
Could the difference be caused by the step pattern you are using? Dtw in R defaults to the symmetric2 step pattern. Explanation of the step pattern from Toni Giorgino's paper:


  symmetric2 is normalizable, symmetric, with no local slope constraints. Since one diagonal step costs as much as the two equivalent steps along the sides, it can be normalized dividing by $N+M$ (query+reference lengths).


I thought this might be the problem after reading Comparing Dynamic Time Warping in R and Python. 

If your problem is the same try adding step=symmetric1 to your R.dtw arguements.