The goal of our evaluation is to ensure fair comparison to other methods and our own. The actual metrics we use can be found on the Filter Evaluation Metrics page. Using our metrics we wish to provide insight into why our method does better and in what ways (as no method will outperform in all aspects). Since we are also interested in applying the systems to real robotic applications, the realtime performance is also a key metric we need to investigate. Timing of different system components is also key to removing bottlenecks and seeing where performance improvements or estimator approximations might help reduce complexity.
The key metrics we are interested in evaluating are the following:
- Absolute Trajectory Error (ATE)
- Relative Pose Error (RPE)
- Root Mean Squared Error (RMSE)
- Normalized Estimation Error Squared (NEES)
- Estimator Component Timing
- System Hardware Usage (memory and computation)