What's the best way to represent accuracy of a (0,0) target I am an undergraduate student doing a research about quadcopter landing accuracy. I read several research about related topics and many of them showing only the Absolue Mean Error (EMA). However my supervisor said that there might be a way to represent the data in terms of accuracy (percentage). The goal is to compare the accuracy of landing position between two different methods, with (0,0) target. I've read about some accuracy metric like MAPE, but still in doubt that this is the appropriate method. And also MAPE does not deal with 0 actual value. So I was wondering if there is any good way to represent the accuracy of these two methods or should I only represent them in Mean Absolute Error (MAE). Below is the example data:

 A: You have coordinates of the landings of quadcopters with a camera (blue squares) and quadcopters without a camera (red circles).  There are two obvious measures of accuracy with the same scale as the observations:

*

*Mean absolute error

*Root mean square error

It will not make much difference which you use in this particular case (every quadcopter with a camera did better than every quadcopter without a camera), but in general when choosing you might want to consider whether big errors are much more serious than small errors (ask yourself whether having one landing $100$cm away and one on the target is worse than having two landings $50$cm away - if so, perhaps choose the root mean square error, but if they are equally bad then consider using the mean absolute error)
I do not really understand your supervisor's comment: relative error or percentage error is more about when you are try to estimate a value and you want to say that  estimating $3$ when the true value is $4$ is as bad as estimating $300$ when the true value is $400$.  But that is not the case here: the desired outcome is on the target (a distance of $0$) and you cannot divide anything by $0$ to get a measure of relative error.
