Physics

Finite impulse response

Mobile robot

Lidar

Gene

Algorithm

Filter (signal processing)

Inertial navigation system

Ranging

Inertial frame of reference

Infinite impulse response

Artificial intelligence

Kalman filter

Geography

Extended Kalman filter

Chemistry

Digital filter

Computer science

Quantum mechanics

Simultaneous localization and mapping

Computer vision

Biochemistry

Remote sensing

Robustness (evolution)

Telecommunications

Robot

IEEE Access

In this paper, an indoor inertial navigation system (INS) integrated with light detection and ranging (LiDAR) robot localization system is proposed to provide accurate information about the robot location. To achieve high accuracy and robustness, a cascaded finite-impulse response (FIR) filter is designed and incorporated into the proposed INS/LiDAR localization scheme. The cascaded scheme employs two FIR filters. An unbiased FIR filter is used to estimate the LiDAR-derived position by fusing distances between a robot and detected corner points. An extended FIR filter is used to fuse the LiDAR- and INS-based measurements. An experimental study indicates that the proposed scheme demonstrates higher robustness than the traditional methods of localization employing Kalman filtering.

Indoor INS/LiDAR-Based Robot Localization With Improved Robustness Using Cascaded FIR Filter