Limited Information Shared Control: A Potential Game Approach

TL;DR

This paper introduces a novel systematic design method for limited information shared control using near potential differential games, effectively modeling human-machine interactions in partially observable systems.

Contribution

It develops a new class of games, NPDG, with conditions and algorithms for designing shared control systems in human-automation scenarios.

Findings

Faster and more accurate controller design compared to manual tuning

Successful application to a vehicle-manipulator system

Validated through simulations and a user study with sixteen subjects

Abstract

This paper presents a systematic method for the design of a limited information shared control (LISC). LISC is used in applications where not all system states or reference trajectories are measurable by the automation. Typical examples are partially human-controlled systems, in which some subsystems are fully controlled by automation while others are controlled by a human. The proposed systematic design method uses a novel class of games to model human-machine interaction: the near potential differential games (NPDG). We provide a necessary and sufficient condition for the existence of an NPDG and derive an algorithm for finding a NPDG that completely describes a given differential game. The proposed design method is applied to the control of a large vehicle-manipulator system, in which the manipulator is controlled by a human operator and the vehicle is fully automated. The suitability of the NPDG to model differential games is verified in simulations, leading to a faster and more accurate controller design compared to manual tuning. Furthermore, the overall design process is validated in a study with sixteen test subjects, indicating the applicability of the proposed concept in real applications.