Human-Like Trajectories Generation via Receding Horizon Tracking Applied to the TickTacking Interface

TL;DR

This paper presents a receding horizon control method to generate human-like trajectories for a rhythm-based interface, improving user interaction by mimicking natural movement behaviors.

Contribution

It introduces a novel controller that incorporates human behavioral features into trajectory generation for rhythm-based interfaces.

Findings

Human-inspired controller outperforms baseline in mimicking natural trajectories

Incorporating behavioral features enhances user performance and interface intuitiveness

The approach reduces interaction frustration in rhythm-based control systems

Abstract

TickTacking is a rhythm-based interface that allows users to control a pointer in a two-dimensional space through dual-button tapping. This paper investigates the generation of human-like trajectories using a receding horizon approach applied to the TickTacking interface in a target-tracking task. By analyzing user-generated trajectories, we identify key human behavioral features and incorporate them in a controller that mimics these behaviors. The performance of this human-inspired controller is evaluated against a baseline optimal-control-based agent, demonstrating the importance of specific control features for achieving human-like interaction. These findings contribute to the broader goal of developing rhythm-based human-machine interfaces by offering design insights that enhance user performance, improve intuitiveness, and reduce interaction frustration