Modeling and performance evaluation of mecanum wheel platform with reduced vibration and a robust path planning - Yadav, Pankaj Singh; Mohanta, J. C.; Agrawal, Vandana; Ahmed, MD. Faiyaz (Journal of the Brazilian Society of Mechanical Sciences and Engineering, 2024)
The mecanum wheelchair robot (MWCR) has gained widespread popularity for its exceptional maneuverability in environments with limited mobility. Despite its advantages, the design of mecanum wheel-equipped wheelchairs faces significant challenges, including issues related to strength, design comple x ity, movement smoothness, and vertical vibrations, all of which directly impact user comfort and maneuverability. This manuscript aims to contribute to the field by addressing these challenges and enhancing the overall performance of mecanum wheelchairs. In pursuit of increased wheelchair mobility and user comfort, we explored five distinct models, each designed to mitigate vibrations. The final model was meticulously chosen based on a comprehensive evaluation of materials used in mecanum wheel design, taking into account strength, deformation, and vibration reduction. This primary objective is integral to improving the user experience and comfort during wheelchair navigation. As a secondary objective, we employed a modified artificial bee colony optimization (MABC) approach for local path planning of a four MWCR in a static environment. Our paper provides a comprehensive analysis, including static, dynamic, and vibration assessments of the mecanum wheel, specifically tailored for indoor navigation. Validation of the proposed MABC optimization involved comparing a theoretical avoidance technique with an experimental procedure under identical conditions. Comparing the proposed mecanum wheel design, incorporating various materials, with an existing model from the literature review our findings reveal a 13.83% increase in strength, reduced deformation, and a 3.297% decrease in vibration. The efficacy of our design, particularly concerning optimal wheelchair design for a specific load capacity, has been rigorously validated through simulations and experimental data. Our research’s secondary objective yielded compelling results, indicating that the MABC-optimized technique, on average, achieves a 5.9% reduction in length and a notable 14.67% improvement in speed. Comparative analyses conclusively demonstrate the superior performance of MABC optimization over traditional ABC optimization. In summary, this research contributes novel insights into the optimal design of mecanum wheelchairs, emphasizing the significance of user comfort and maneuverability.