Generalized Shared Control versus Classical Shared Control: Illustrative Examples

TL;DR

This paper compares classical and generalized shared control methods, demonstrating that GSC better handles multimodal uncertainties to improve safety, efficiency, and operator-autonomy agreement in complex robotic scenarios.

Contribution

It introduces a novel generalized shared control approach that optimally manages multimodal uncertainties, enhancing safety and operator-autonomy alignment.

Findings

GSC prevents unsafe shared control in multimodal conditions

GSC improves safety and efficiency over classical methods

Illustrations clarify the advantages of GSC

Abstract

Shared control fuses operator inputs and autonomy inputs into a single command. However, if environmental or operator predictions are multimodal, state of the art approaches are suboptimal with respect to safety, efficiency, and operator-autonomy agreement: even under mildly challenging conditions, existing approaches can fuse two safe inputs into an unsafe shared control [13]. Multi-modal conditions are common to many real world applications, such as search and rescue robots navigating disaster zones, teleoperated robots facing communication degradation, and assistive driving technologies. In [11, 13], we introduced a novel approach called generalized shared control (GSC) that simultaneously optimizes autonomy objectives (e.g., safety and efficiency) and operator-autonomy agreement under multimodal conditions; this optimality prevents such unsafe shared control. In this paper, we describe those results in more user friendly language by using illustrations and text.