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Twisting for soft intelligent autonomous robot in unstructured environments.
Zhao, Yao; Chi, Yinding; Hong, Yaoye; Li, Yanbin; Yang, Shu; Yin, Jie.
Afiliação
  • Zhao Y; Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695.
  • Chi Y; Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695.
  • Hong Y; Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695.
  • Li Y; Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695.
  • Yang S; Department of Materials Science and Engineering, University of Pennsylvania, Philadelphia, PA 19104.
  • Yin J; Department of Mechanical and Aerospace Engineering, North Carolina State University, Raleigh, NC 27695.
Proc Natl Acad Sci U S A ; 119(22): e2200265119, 2022 05 31.
Article em En | MEDLINE | ID: mdl-35605115
Soft robots that can harvest energy from environmental resources for autonomous locomotion is highly desired; however, few are capable of adaptive navigation without human interventions. Here, we report twisting soft robots with embodied physical intelligence for adaptive, intelligent autonomous locomotion in various unstructured environments, without on-board or external controls and human interventions. The soft robots are constructed of twisted thermal-responsive liquid crystal elastomer ribbons with a straight centerline. They can harvest thermal energy from environments to roll on outdoor hard surfaces and challenging granular substrates without slip, including ascending loose sandy slopes, crossing sand ripples, escaping from burying sand, and crossing rocks with additional camouflaging features. The twisting body provides anchoring functionality by burrowing into loose sand. When encountering obstacles, they can either self-turn or self-snap for obstacle negotiation and avoidance. Theoretical models and finite element simulation reveal that such physical intelligence is achieved by spontaneously snapping-through its soft body upon active and adaptive soft body-obstacle interactions. Utilizing this strategy, they can intelligently escape from confined spaces and maze-like obstacle courses without any human intervention. This work presents a de novo design of embodied physical intelligence by harnessing the twisting geometry and snap-through instability for adaptive soft robot-environment interactions.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Robótica Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Robótica Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article