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

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An Admittance Control Method Based on Parameters Fuzzification for Humanoid Steering Wheel Manipulation.

Tuochang Wu¹, Junkai Ren¹, Chuang Cheng¹

¹College of Intelligence Science and Technology, National University of Defense Technology, 109 Deya Road, Kaifu District, Changsha 410073, China.

Biomimetics (Basel, Switzerland)

|October 27, 2023

Summary

This study introduces a 7-DOF humanoid bionic manipulator with a novel wrist design for human-like steering. An admittance control approach with parameter fuzzification ensures stable and compliant steering, even in extreme configurations.

Keywords:

admittance control humanoid manipulation parameter fuzzification steering wheel manipulation

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Area of Science:

Robotics
Humanoid Robotics
Bionic Engineering

Background:

Developing humanoid robots with human-like behavioral skills is a significant challenge.
Enabling robots to perform complex tasks like driving a vehicle requires advanced manipulation capabilities.

Purpose of the Study:

To design a novel 7-DOF humanoid bionic manipulator capable of human-like steering.
To apply and adapt an admittance control approach for stable and compliant steering wheel manipulation.

Main Methods:

A 7-DOF humanoid manipulator was designed with a 3-2-2 motor arrangement and modified wrist structure.
An admittance control approach was implemented, incorporating parameter fuzzification to handle system variations.
Simulations were conducted in Coppeliasim to validate the control strategy.

Main Results:

The proposed admittance control with parameter fuzzification achieved compliant force control under extreme configurations.
The humanoid manipulator demonstrated stable steering wheel operation even in challenging scenarios.
This represents the first use of admittance control for human-like steering wheel operation by a manipulator.

Conclusions:

The developed humanoid bionic manipulator and control strategy are effective for human-like steering.
The approach offers a promising solution for advanced robotic manipulation in automotive applications.
Further research can explore real-world implementation and more complex driving tasks.