This is a good question which arises in slightly different forms in a wide array of problems. One example: how to average an ensemble of GPS position recordings, each of which corresponds to the same course. Another (from my work): find th average hip or knee angle (in 3D), over one stride, when you have a recording of a person walking for many strides on a treadmill, and the stride lengths and durations vary somewhat.
I assume the recordngs do not all have the same number of points.
Resample each vector to have 1000 elements, using interp1(), then average them with mean().
This is probably the best approach in the absence of ther information.
The most obvious "other information" would be a time stamp for each position. If your data is sampled at uniform intervals, then the array index is a time stamp. If you want the average position at each time, and if the recordings are of varying length, then pad at the beginning with the initial position, or pad at the end with the final position, to get vectors of uniform length, then average them. You said you did something like this and the results were bad. But I don't know how you padded. A different padding choice could help.