Enhancing Sliding Performance with Aerial Robots: Analysis and Solutions for Non-Actuated Multi-Wheel Configurations

TL;DR

This paper investigates the challenges of sliding tasks performed by aerial robots with non-actuated multi-wheel end-effectors, proposing mechanical and control solutions validated through experiments and simulation for improved performance.

Contribution

It provides the first in-depth analysis of contact conditions in sliding tasks with multi-wheel aerial robot end-effectors and introduces a pressure-sensing control framework.

Findings

Mechanical design guidelines derived from experimental data.

A novel pressure-sensing control framework for reliable sliding.

Validated improvements in sliding performance through simulation.

Abstract

Sliding tasks performed by aerial robots are valuable for inspection and simple maintenance tasks at height, such as non-destructive testing and painting. Although various end-effector designs have been used for such tasks, non-actuated wheel configurations are more frequently applied thanks to their rolling capability for sliding motion, mechanical simplicity, and lightweight design. Moreover, a non-actuated multi-wheel (more than one wheel) configuration in the end-effector design allows the placement of additional equipment e.g., sensors and tools in the center of the end-effector tip for applications. However, there is still a lack of studies on crucial contact conditions during sliding using aerial robots with such an end-effector design. In this article, we investigate the key challenges associated with sliding operations using aerial robots equipped with multiple non-actuated wheels through in-depth analysis grounded in physical experiments. The experimental data is used to create a simulator that closely captures real-world conditions. We propose solutions from both mechanical design and control perspectives to improve the sliding performance of aerial robots. From a mechanical standpoint, design guidelines are derived from experimental data. From a control perspective, we introduce a novel pressure-sensing-based control framework that ensures reliable task execution, even during sliding maneuvers. The effectiveness and robustness of the proposed approaches are then validated and compared using the built simulator, particularly in high-risk scenarios.