A Hybrid Approach for Trajectory Control Design

This work presents a methodology to design trajectory tracking feedback control laws, which embed non-parametric statistical models, such as Gaussian Processes (GPs). The aim is to minimize unmodeled dynamics such as undesired slippages. The proposed approach has the benefit of avoiding complex terr...

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Published in:arXiv.org 2022-11
Main Authors: Freda, Luigi, Gianni, Mario, Pirri, Fiora
Format: Article
Language:English
Subjects:
Computer simulation
Feedback control
Gaussian process
Robot dynamics
Statistical models
Tracking control
Trajectory control
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Gianni, Mario
Pirri, Fiora
description This work presents a methodology to design trajectory tracking feedback control laws, which embed non-parametric statistical models, such as Gaussian Processes (GPs). The aim is to minimize unmodeled dynamics such as undesired slippages. The proposed approach has the benefit of avoiding complex terramechanics analysis to directly estimate from data the robot dynamics on a wide class of trajectories. Experiments in both real and simulated environments prove that the proposed methodology is promising.
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subjects Computer simulation
Feedback control
Gaussian process
Robot dynamics
Statistical models
Tracking control
Trajectory control
title A Hybrid Approach for Trajectory Control Design
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