A hybrid EKF/KF state estimator for a skid-steered ATV

Abstract

This article presents a novel state estimation structure developed for a skid-steered, six-wheeled, ARGO® all-terrain vehicle (ATV). The ARGO ATV is a teleoperated unmanned ground vehicle custom fitted with an inertial measurement unit, wheel encoders and a Geographic Positioning System (GPS). This paper offers the following contributions: (1) a hybrid extended Kalman filter/Kalman filter state estimation technique that estimates the motion, orientation and wheel slips for an ARGO and (2) a virtual GPS point generation algorithm that can be used to adjust position estimates using a GPS sensor. Our field experiments reveal that the proposed estimation structure is able to estimate the position, velocity, orientation and longitudinal slip of the ARGO with a reasonable amount of accuracy. In addition, the proposed estimation structure is well suited for online applications and can also incorporate offline virtual GPS data to further improve the accuracy of the position estimates. The proposed estimation structure is also capable of estimating the longitudinal slip for every wheel of the ARGO.

Slip-Aware Motion Estimation for Off-Road Mobile Robots via Multi-Innovation Unscented Kalman Filter

“…The estimation accuracy suffered from increasing navigating speed, longer distance, and conventional GPS. In [24], a hybrid scheme of EKF and KF was proposed to estimate the position and velocity of a 6-wheel skid-steered vehicle while only the longitudinal wheel slip was modeled. Recently, Wang et al [25] introduced an innovation-based EKF combined with Bayesian filter for robot navigating on various terrains.…”

“…2. The sensing system in this paper uses a Dual Antenna GNSS alongside with an IMU and two encoders mounted on two driven motors, which is a more standard approach for this category of off-road robots [24]. Furthermore, in the indoor and outdoor environment, it is most desirable to design an estimator accurately tracking the position only with proprioceptive sensors such as encoders and IMU.…”

“…The fact that errors will accumulate if there are no exteroceptive sensors to correct localization makes the GNSS indispensable in outdoor applications, especially on a long journey. As a result, some researchers proposed a hierarchical estimator using several KFs [24].…”

Performance Analysis of EKF and UKF for Estimating Tire Longitudinal and Side Angle Slip

“…The characteristic of slip in this situation is as follows: low constant longitudinal slip, gradually increase and then decrease side angle slip (represented by a parabola [4]). For gradual cornering, longitudinal slip has also insignificant characteristic.…”

“…Therefore, many researches have been proposed to reduce the cost. In [3], [4], GPS (Global Positioning System) and INS (Inertial Navigation System) sensors are used to estimate vehicle tire slips. And a different algorithm or method have been suggested for more accurate estimation in [5].…”