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The modularization design and autonomous motion control of a new baby stroller.
Zhang, Chunhong; He, Zhuoting; He, Xiaotong; Shen, Weifeng; Dong, Lin.
Affiliation
  • Zhang C; School of Art and Design, University of Electronic Science and Technology of China, Zhongshan Institute, Zhongshan, China.
  • He Z; School of Art and Design, University of Electronic Science and Technology of China, Zhongshan Institute, Zhongshan, China.
  • He X; Weihai Institute for Bionics, Jilin Univerisity, Weihai, China.
  • Shen W; College of Building Engineering, Xiamen City University, Xiamen, China.
  • Dong L; Center on Frontiers of Computing Studies, Peking University, Beijing, China.
Front Hum Neurosci ; 16: 1000382, 2022.
Article in En | MEDLINE | ID: mdl-36248687
ABSTRACT
The increasing number of newborns has stimulated the infant market. In particular, the baby stroller, serving as an important life partner for both babies and parents, has attracted more attention from society. Stroller design and functionality are of vital importance to babies' physiological and psychological health as well as brain development. Therefore, in this paper, we propose a modularization design method for the novel four-wheeled baby stroller based on the KANO model to ensure the mechanical safety and involve more functionalities. Manual control of the baby stroller requires the rapid response of human motor systems in a completely controlled manner, which could be a potential risk. To enhance the safety and stability of the stroller motion, especially in situations where manual control is hard to achieve (e.g., sharp turns), we propose an autonomous motion control scheme based on model predictive control. Both the modularization design and the motion controller are verified in the MATLAB simulation environment through path tracking tasks. The feasibility is validated by the satisfactory experimental results with lateral position error in a reasonable range and good trajectory smoothness.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Front Hum Neurosci Year: 2022 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Front Hum Neurosci Year: 2022 Document type: Article Affiliation country: China