Adaptive particle filter to reduce the pose estimation problem to achieve time-efficient navigation of UGV
Himanshi Bhargav, Ravinder Pal Singh · International Journal of Nonlinear Dynamics and Control · 2023
The proposed research focuses on designing an adaptive filter based on the particle filter in which the number of particles has been optimised by considering the complexity factor of the environment and a mathematical relation for finding out the environment's complexity designed to achieve reliable pose estimation. The performance of traditional particle filters suffers from the time/space complexity, resulting in the time lag problem during the autonomous navigation of vehicles. The proposed adaptive filter is tried and tested in various simulated experiments and it is experimentally obtained that it reduces the computational load by 5.22% and the error in the predicted and actual measurement model is also reduced by 19.66% w.r.t to low complexity environment, 16.05% w.r.t medium complexity environment and 15.35% w.r.t high complexity environment. The proposed technique is applicable in the various subfield of unmanned ground vehicles such as path planning, trajectory tracking problems, autonomous navigation, etc.