Enabling Shared-Control for A Riding Ballbot System

TL;DR

This paper presents PURE, a shared-control system for a self-balancing riding ballbot that enhances collision avoidance and navigation through a novel PAPF method, tested with human users to demonstrate safety and intuitiveness.

Contribution

The study introduces a new shared-control approach with PAPF for a riding ballbot, improving collision avoidance and user experience over traditional methods.

Findings

Shared-control reduced collisions and cognitive load.

Navigation remained efficient with no speed reduction.

Effective for indoor obstacle avoidance in mobility devices.

Abstract

This study introduces a shared-control approach for collision avoidance in a self-balancing riding ballbot, called PURE, marked by its dynamic stability, omnidirectional movement, and hands-free interface. Integrated with a sensor array and a novel Passive Artificial Potential Field (PAPF) method, PURE provides intuitive navigation with deceleration assistance and haptic/audio feedback, effectively mitigating collision risks. This approach addresses the limitations of traditional APF methods, such as control oscillations and unnecessary speed reduction in challenging scenarios. A human-robot interaction experiment, with 20 manual wheelchair users and able-bodied individuals, was conducted to evaluate the performance of indoor navigation and obstacle avoidance with the proposed shared-control algorithm. Results indicated that shared-control significantly reduced collisions and cognitive load without affecting travel speed, offering intuitive and safe operation. These findings highlight the shared-control system's suitability for enhancing collision avoidance in self-balancing mobility devices, a relatively unexplored area in assistive mobility research.