Error Scaling in Position Estimation from Noisy Relative Pose Measurements
نویسندگان
چکیده
We examine how fast the estimation error grows with time when a mobile robot/vehicle estimates its location from relative pose measurements without global position or orientation sensors. We show that both bias and variance of the position estimation error grows at most linearly with time (or distance traversed) asymptotically. The bias growth rate is crucially dependent on the trajectory of the robot. An exact formula for the error bias is provided for a special case of a periodic trajectory in 2-D. Experiments with a P3-DX wheeled robot and Monte-Carlo simulations are provided to verify the theoretical predictions.
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