Biotensegrity, which integrates tensegrity principles with biological structures, describes how living organisms efficiently distribute mechanical forces to accommodate stresses. This chapter provides an overview of biotensegrity in anatomy and physiology, spanning from the macro to the micro level of a living organism. The chapter details the development of a biotensegrity model that replicates the tapered vertebral bodies and natural curvature of the human spine. A form-finding method for generating an n-stage three-strut spine model using static equilibrium equations is presented. Shape change strategies are explored using Sequential Quadratic Programming (SQP), enabling identified monitored nodes to move from their initial positions to target coordinates by adjusting cable lengths. Additionally, an obstacle avoidance strategy based on the Potential Method facilitates flexible motion, allowing the model to reach target positions while navigating around obstacles. Comparative results highlight the influence of obstacle avoidance considerations. The chapter concludes with insights into future research directions, emphasizing biotensegrity’s potential applications in biomechanics, robotics, and structural design.

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Shape Control for Biotensegrities

  • Chai Lian Oh,
  • Kok Keong Choong,
  • Toku Nishimura

摘要

Biotensegrity, which integrates tensegrity principles with biological structures, describes how living organisms efficiently distribute mechanical forces to accommodate stresses. This chapter provides an overview of biotensegrity in anatomy and physiology, spanning from the macro to the micro level of a living organism. The chapter details the development of a biotensegrity model that replicates the tapered vertebral bodies and natural curvature of the human spine. A form-finding method for generating an n-stage three-strut spine model using static equilibrium equations is presented. Shape change strategies are explored using Sequential Quadratic Programming (SQP), enabling identified monitored nodes to move from their initial positions to target coordinates by adjusting cable lengths. Additionally, an obstacle avoidance strategy based on the Potential Method facilitates flexible motion, allowing the model to reach target positions while navigating around obstacles. Comparative results highlight the influence of obstacle avoidance considerations. The chapter concludes with insights into future research directions, emphasizing biotensegrity’s potential applications in biomechanics, robotics, and structural design.