Conjugated Capabilities: Interrelations of Elementary Human Capabilities and Their Implication on Human-Machine Task Allocation and Capability Testing Procedures

TL;DR

This paper introduces the concept of conjugated capabilities, analyzing their interrelations to improve human-machine task allocation and capability testing, with applications in manufacturing and rehabilitation.

Contribution

It defines and analyzes conjugated capabilities, demonstrating their interrelations within the IMBA standard and applying this understanding to optimize testing and task allocation.

Findings

Evidence of conjugated capabilities in post-rehabilitation data

A network model of interrelated capabilities for manufacturing tasks

Potential to enhance human-autonomy collaboration efficiency

Abstract

Human and automation capabilities are the foundation of every human-autonomy interaction and interaction pattern. Therefore, machines need to understand the capacity and performance of human doing, and adapt their own behavior, accordingly. In this work, we address the concept of conjugated capabilities, i.e. capabilities that are dependent or interrelated and between which effort can be distributed. These may be used to overcome human limitations, by shifting effort from a deficient to a conjugated capability with performative resources. For example: A limited arm's reach may be compensated by tilting the torso forward. We analyze the interrelation between elementary capabilities within the IMBA standard to uncover potential conjugation, and show evidence in data of post-rehabilitation patients. From the conjugated capabilities, within the example application of stationary manufacturing, we create a network of interrelations. With this graph, a manifold of potential uses is enabled. We showcase the graph's usage in optimizing IMBA test design to accelerate data recordings, and discuss implications of conjugated capabilities on task allocation between the human and an autonomy.