A general compensation control method for human–robot integration

This paper introduces a new generalized control method designed for multi-degrees-of-freedom (DoF) devices to help people with limited motion capabilities in their daily activities. The challenge lies in finding the most adapted strategy for the control interface to effectively map the user’s motions in a low-dimensional space to complex robotic assistive devices, such as prostheses, supernumerary limbs, and even remote robotic avatars. The goal is a system that integrates the human and the robotic parts into a unique system, moving to reach the targets decided by the human while autonomously reducing the user’s effort and discomfort. We present a framework to control general multi-DoFs assistive systems, which translates user-performed compensatory motions into the necessary robot commands for reaching targets while canceling or reducing compensation. The framework extends to prostheses of any number of DoFs up to full robotic avatars, regarded here as a sort of “whole-body prosthesis” of the person who sees the robot as an artificial extension of their own body without a physical link but with a sensory-motor integration. We have validated and applied this control strategy through tests encompassing simulated scenarios and real-world trials involving a virtual twin of the robotic parts (prosthesis and robot) and a physical humanoid avatar.

Authors

Institutions

Publication Details

Journal
The International Journal of Robotics Research
Published
2025-05-30
DOI
https://doi.org/10.1177/02783649251344636
Primary Topic
Muscle activation and electromyography studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A general compensation control method for human–robot integration

Manuel G. Catalano, Maddalena Feder, Giorgio Grioli, Antonio Bicchi
The International Journal of Robotics Research
Muscle activation and electromyography studies
article

A general compensation control method for human–robot integration

Manuel G. Catalano, Maddalena Feder, Giorgio Grioli, Antonio Bicchi
article en

Abstract

This paper introduces a new generalized control method designed for multi-degrees-of-freedom (DoF) devices to help people with limited motion capabilities in their daily activities. The challenge lies in finding the most adapted strategy for the control interface to effectively map the user’s motions in a low-dimensional space to complex robotic assistive devices, such as prostheses, supernumerary limbs, and even remote robotic avatars. The goal is a system that integrates the human and the robotic parts into a unique system, moving to reach the targets decided by the human while autonomously reducing the user’s effort and discomfort. We present a framework to control general multi-DoFs assistive systems, which translates user-performed compensatory motions into the necessary robot commands for reaching targets while canceling or reducing compensation. The framework extends to prostheses of any number of DoFs up to full robotic avatars, regarded here as a sort of “whole-body prosthesis” of the person who sees the robot as an artificial extension of their own body without a physical link but with a sensory-motor integration. We have validated and applied this control strategy through tests encompassing simulated scenarios and real-world trials involving a virtual twin of the robotic parts (prosthesis and robot) and a physical humanoid avatar.

The International Journal of Robotics Research
University of Pisa (IT), Piaggio (Italy) (IT), Italian Institute of Technology (IT)
Openalex Percentile: Top 89%
Muscle activation and electromyography studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.