RWD-DOF: a dual-degree-of-freedom reconfigurable wheel design for improved robotic mobility

Wheeled mobile robots are efficient on flat surfaces but face limitations in overcoming obstacles like steps due to their fixed wheel radius. This paper presents a novel modular reconfigurable wheel with a dual-degree-of-freedom active reconfigurable mechanism, designed to adapt dynamically to varying step sizes. The wheel's structure includes three curved segments, whose synchronized motion is driven by five-bar linkages and two planetary gear systems. By analyzing the kinematic constraints and both forward and inverse kinematics of the reconfigurable wheel, we established the range of dimensions it can surmount over steps, specifically focusing on height and depth, as well as the relationship with the output angles <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>q</mml:mi> <mml:mn>1</mml:mn></mml:msub> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>q</mml:mi> <mml:mn>2</mml:mn></mml:msub> </mml:math> of the two motors driving the reconfiguration. Simulations using ADAMS software demonstrates the wheel's capability to maintain smooth, continuous center-of-mass movement over steps and stairs. Moreover, physical prototype testing further confirms the feasibility and advantages of the proposed wheel structure. This adaptive design significantly enhances the performance of wheeled robots in navigating complex environments, offering promising potential for applications in challenging terrain.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-05-10
DOI
https://doi.org/10.1038/s41598-025-98239-x
Citations
2
Primary Topic
Robotic Locomotion and Control
Type
article
Field-Weighted Citation Impact
1.35
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

RWD-DOF: a dual-degree-of-freedom reconfigurable wheel design for improved robotic mobility

Feng Tong, HengAn Wu, Yanlong Wei, Chao Wang et al.
2 citations
Scientific Reports
Robotic Locomotion and Control
1.35
article

RWD-DOF: a dual-degree-of-freedom reconfigurable wheel design for improved robotic mobility

Feng Tong, HengAn Wu, Yanlong Wei, Chao Wang, Yanjie Liu
article en
2 citations

Abstract

Wheeled mobile robots are efficient on flat surfaces but face limitations in overcoming obstacles like steps due to their fixed wheel radius. This paper presents a novel modular reconfigurable wheel with a dual-degree-of-freedom active reconfigurable mechanism, designed to adapt dynamically to varying step sizes. The wheel's structure includes three curved segments, whose synchronized motion is driven by five-bar linkages and two planetary gear systems. By analyzing the kinematic constraints and both forward and inverse kinematics of the reconfigurable wheel, we established the range of dimensions it can surmount over steps, specifically focusing on height and depth, as well as the relationship with the output angles <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>q</mml:mi> <mml:mn>1</mml:mn></mml:msub> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>q</mml:mi> <mml:mn>2</mml:mn></mml:msub> </mml:math> of the two motors driving the reconfiguration. Simulations using ADAMS software demonstrates the wheel's capability to maintain smooth, continuous center-of-mass movement over steps and stairs. Moreover, physical prototype testing further confirms the feasibility and advantages of the proposed wheel structure. This adaptive design significantly enhances the performance of wheeled robots in navigating complex environments, offering promising potential for applications in challenging terrain.

Scientific ReportsVol. 15(1)
Harbin Institute of Technology (CN)
Openalex Percentile: Top 20%
Robotic Locomotion and Control
1.35
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.