Purely idle curiosity – I've heard a lot about the Kalman filter over the years, it's a popular subject here, but what are the other filters in the standard robotics toolkit?
Also common in robotics applications is the Particle Filter, which uses a Monte Carlo approximation of the uncertainty in the state, rather than enforcing a (Gaussian) distribution, as in the traditional Kalman filter. This can be useful when the mechanics are highly nonlinear and/or your measurement uncertainties are, well, very non-Gaussian. Sebastian Thrun (a CMU robotics professor in the DARPA "Grand Challenge" days of self-driving cars) made an early Udacity course on Particle Filters.