Nonlinear Unknown Input and State Estimation Algorithm in Mobile Robots

TL;DR

This paper introduces a novel nonlinear estimation algorithm (NUISE) for mobile robots that detects and quantifies sensor and actuator anomalies using sensor data and control commands, applicable to real-world nonlinear dynamic models.

Contribution

The paper presents a new nonlinear unknown input and state estimation algorithm tailored for mobile robots with stochastic noise and nonlinear dynamics.

Findings

Demonstrates application on two different mobile robot models

Effectively detects sensor and actuator anomalies

Handles nonlinear dynamic models with stochastic noise

Abstract

This technical report provides the description and the derivation of a novel nonlinear unknown input and state estimation algorithm (NUISE) for mobile robots. The algorithm is designed for real-world robots with nonlinear dynamic models and subject to stochastic noises on sensing and actuation. Leveraging sensor readings and planned control commands, the algorithm detects and quantifies anomalies on both sensors and actuators. Later, we elaborate the dynamic models of two distinctive mobile robots for the purpose of demonstrating the application of NUISE. This report serves as a supplementary document for [1].