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WheelCon: A Wheel Control-Based Gaming Platform for Studying Human Sensorimotor Control

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A Lyapunov-Stable Adaptive Method to Approximate Sensorimotor Models for Sensor-Based Control.

David Navarro-Alarcon¹, Jiaming Qi¹, Jihong Zhu²

¹The Hong Kong Polytechnic University, Hong Kong, Hong Kong.

Frontiers in Neurorobotics

|October 12, 2020

Summary

This summary is machine-generated.

This study introduces a novel robot control method using only feedback signals to approximate unknown models. The approach efficiently estimates sensorimotor maps with minimal data and guarantees stability.

Keywords:

adaptive systems robotics sensor-based control sensorimotor models servomechanisms visual servoing

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Area of Science:

Robotics
Control Theory
Machine Learning

Background:

Accurate robot models are crucial for effective control.
Estimating sensorimotor models, especially in uncalibrated systems, presents significant challenges.
Traditional methods often require extensive data and lack rigorous stability guarantees.

Purpose of the Study:

To develop a novel scheme for approximating unknown robot sensorimotor models using only feedback signals.
To address the uncalibrated sensor-based regulation problem.
To create an efficient and stable model estimation method.

Main Methods:

Formulation of the uncalibrated sensor-based regulation problem.
Development of a computational method distributing model estimation among specialized adaptive units.
Analytical determination of data requirements for training and constraining the model.
Derivation of conditions for Lyapunov stability.

Main Results:

A new scheme for approximating unknown sensorimotor models using feedback signals.
A computational method that breaks down model estimation into local map specializations.
Demonstration of minimal data requirements for training and model constraints.
Rigorous derivation of stability conditions.

Conclusions:

The proposed method effectively approximates unknown robot sensorimotor models with limited data.
The distributed adaptive unit approach offers an efficient solution for uncalibrated systems.
The method ensures rigorous stability properties, validated by simulations and experiments.