Dan Simon

Towards Robust State Estimation by Boosting the Maximum Correntropy\n Criterion Kalman Filter with Adaptive Behaviors

2021 · arXiv (Cornell University)

This work proposes a resilient and adaptive state estimation framework for\nrobots operating in perceptually-degraded environments. The approach, called\nAdaptive Maximum Correntropy Criterion Kalman Filtering (AMCCKF), is inherently\nrobust to corrupted measurements, such as those containing jumps or …