Selecting haptic guidance models in teleoperation: guidelines from a comparative user study

2026-06-02

AI Summary

This study addresses the absence of systematic guidelines for selecting haptic guidance models tailored to specific tasks, environments, and operators in teleoperation. The authors propose a unified stiffness-damping modeling framework that expresses prominent approaches—including spring-damper systems, potential fields, and guidance tubes—as instances defined by specific guidance functions. A user study conducted in vertical farming scenarios evaluates the performance of these models across six distinct environments. By introducing an environment-aware model selection guideline and novel objective interaction metrics, the work demonstrates that guidance force magnitude significantly influences operator comfort and trust. Findings reveal no universally optimal model: spring-damper systems excel in cluttered settings, potential fields perform well in open spaces but pose risks near obstacles, and guidance tubes offer a robust compromise, thereby providing actionable criteria for practical deployment.

Abstract

Haptic guidance in teleoperation enhances operator performance through force feedback. This paper presents guidelines to select the most appropriate model considering the task, the environment and the operator. We define a unified formulation expressing most common models (spring-damper, potential field, and guiding tube) as variations of a stiffness-damping system with model-specific guiding functions. We conducted a user study comparing the three classical models across six scenarios with varying environmental conditions in a vertical farming task. Results show no universally superior model: spring-damper excels in cluttered environments, potential field in free spaces (but it shows risks near obstacles), and guiding tube offers a balanced compromise. We propose novel objective metrics to evaluate the interaction, and show that guiding force magnitude correlates with comfort and trust scores. These findings provide practical model selection guidelines through environmental characteristics and real-time evaluation metrics.

Problem

• haptic guidance
• teleoperation
• model selection
• force feedback
• user study

Innovation

• haptic guidance
• teleoperation
• unified formulation
• user study
• objective metrics