Robust Tube-based Model Predictive Control for Time-constrained Robot Navigation

TL;DR

This paper introduces a robust tube-based NMPC framework for time-constrained robot navigation with uncertain nonlinear dynamics, ensuring high-level temporal logic specifications are satisfied.

Contribution

It develops a novel control scheme combining online FHOCP and offline backstepping to guarantee trajectory containment and satisfy MITL specifications.

Findings

Framework guarantees satisfaction of complex temporal logic specifications.

Numerical simulations validate the effectiveness of the proposed control scheme.

The approach handles nonlinear uncertainties and time constraints effectively.

Abstract

This paper deals with the problem of time-constrained navigation of a robot modeled by uncertain nonlinear non-affine dynamics in a bounded workspace of $\mathbb{R}^n$. Initially, we provide a novel class of robust feedback controllers that drive the robot between Regions of Interest (RoI) of the workspace. The control laws consists of two parts: an on-line controller which is the outcome of a Finite Horizon Optimal Control Problem (FHOCP); and a backstepping feedback law which is tuned off-line and guarantees that the real trajectory always remains in a bounded hyper-tube centered along the nominal trajectory of the robot. The proposed controller falls within the so-called tube-based Nonlinear Model Predictive control (NMPC) methodology. Then, given a desired high-level specification for the robot in Metric Interval Temporal Logic (MITL), by utilizing the aforementioned controllers, a framework that provably guarantees the satisfaction of the formula is provided. The proposed framework can handle the rich expressiveness of MITL in both safety and reachability specifications. Finally, the proposed framework is validated by numerical simulations.