Development and Performance Analysis of a Four-Wheeled Wall Climbing Robot Using Dual EDF-Based Adhesion System Article

Telusma, Mackenson, Yulkowski, Kevin, Abrahao, Anthony et al. (2026). Development and Performance Analysis of a Four-Wheeled Wall Climbing Robot Using Dual EDF-Based Adhesion System . APPLIED SCIENCES-BASEL, 16(12), 5931-5931. 10.3390/app16125931

cited authors

  • Telusma, Mackenson; Yulkowski, Kevin; Abrahao, Anthony; McDaniel, Dwayne; Lagos, Leonel

abstract

  • The deployment of wall-climbing robotic systems plays an important role for executing inspection and maintenance tasks in high-risk environments and minimizing the risk to operators tasked with the inspection. Conventional adhesion techniques, such as magnetic, suction, and dry adhesives, encounter significant challenges when applied to diverse surface types. This study presents a four-wheeled robotic platform utilizing dual electric ducted fans (EDFs) to produce adjustable adhesion forces, facilitating uninterrupted movement from horizontal to vertical planes. A comprehensive multibody dynamics model constructed using MSC Adams analyzed wheel–surface interaction, thrust forces, and system stability during transitional phases, revealing essential force parameters for stable vertical operation and determining minimum thrust levels required to sustain four-point contact during orthogonal transitions. These findings informed thrust distribution optimization between the two EDF units to reduce rotational effects while ensuring sufficient safety margins during the ground to vertical wall transition. The findings also allowed for appropriate thrust application ensuring the generation of the required normal force distribution at wheel contact interfaces during vertical movement. A physical prototype was developed and experimentally validated, demonstrating dependable adhesion and maneuverability across a spectrum of orientations and highlighting the efficacy of simulation-driven design for thrust-based adhesion systems.

publication date

  • June 11, 2026

published in

Digital Object Identifier (DOI)

publisher

  • MDPI AG

start page

  • 5931

end page

  • 5931

volume

  • 16

issue

  • 12