Indoor Navigation Using Information From A Map And A Rangefinder
This work addresses indoor navigation for mobile objects, but appears incremental as it builds on existing Bayesian filtering methods without claiming broad breakthroughs.
The paper tackles indoor navigation for mobile objects by formulating a nonlinear filtering problem to optimally estimate parameters using a map and distance measurements, and presents a point-mass method algorithm with simulation results demonstrating its advantages.
The problem of indoor navigation of mobile objects, using a map and measurements of distances to the walls is considered. A nonlinear filtering problem aimed at calculating the optimal, in the root-mean-square sense, of the sought parameters is formulated in the context of the Bayesian approach. The algorithm for its solution based on the point-mass method is described. The simulation results illustrating the advantages of the proposed problem statement and the resultant algorithm are discussed.