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Effect of underactuated parallelogram shape-shifting for environmental adaptation movement of a three modular in-pipe robot.
Kakogawa, Atsushi; Ma, Shugen.
Afiliación
  • Kakogawa A; Department of Robotics, Ritsumeikan University, Kusatsu, Shiga, Japan.
  • Ma S; Department of Robotics, Ritsumeikan University, Kusatsu, Shiga, Japan.
Front Robot AI ; 10: 1234835, 2023.
Article en En | MEDLINE | ID: mdl-37810203
This paper presents an in-pipe robot with three underactuated parallelogram crawler modules, which can automatically shift its body shape when encountering obstacles. The shape-shifting movement is achieved by only a single actuator through a simple differential mechanism by only combining a pair of spur gears. It can lead to downsizing, cost reduction, and simplification of control for adaptation to obstacles. The parallelogram shape does not change the total belt circumference length, thus, a new mechanism to maintain the belt tension is not necessary. Moreover, the proposed crawler can form the anterior-posterior symmetric parallelogram relative to the moving direction, which generates high adaptability in both forward and backward directions. However, whether the locomotion or shape-shifting is driven depends on the gear ratio of the differential mechanism because their movements are only switched mechanically. Therefore, to clarify the requirements of the gear ratio for the passive adaptation, two outputs of each crawler mechanism (torques of the flippers and front pulley) are quasi-statically analyzed, and how the environmental and design parameters influence the robot performance are verified by real experiments. From the experiments, although the robot could not adapt to the stepped pipe in vertical section, it successfully shifted its crawler's shape to parallelogram in horizontal section only with our simulated output ratio.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Robot AI Año: 2023 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Suiza

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Front Robot AI Año: 2023 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Suiza