# SpiRobs: Logarithmic Spiral-shaped Robots for Versatile Grasping Across Scales

arXiv: https://arxiv.org/abs/2303.09861 · HTML: https://mlsanity.com/paper/2303.09861/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Mar 2023.

## Built on by (most cited first, 6 of 6)

- [A Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AI](https://mlsanity.com/paper/2505.01458/) (2025)
- [Mastering Contact-rich Tasks by Combining Soft and Rigid Robotics with Imitation Learning](https://mlsanity.com/paper/2410.07787/) (2024)
- [Diverse and Adaptable Arm Coordination for Octopus-Crawling via Diffusion-Based Uncertainty-Aware Optimization](https://mlsanity.com/paper/2609.21138/) (2026)
- [Reinforcement learning in linear embedding space unlocks generalizable control across soft robot configurations](https://mlsanity.com/paper/2606.08104/) (2026)
- [Whole-Body Semantic-to-Actuation Grounding of Elephant-Inspired Soft-Trunk Motion via Lightweight Flow Matching](https://mlsanity.com/paper/2607.11018/) (2026)
- [History-Conditioned Flow Matching for Probabilistic Dynamics of Tendon-Driven Continuum Robots](https://mlsanity.com/paper/2609.25658/) (2026)

## Abstract (arXiv)

Realizing a soft manipulator with biologically comparable flexibility and versatility often requires careful selection of materials and actuation, as well as attentive design of its structure, perception, and control. Here, we report a new class of soft robots (SpiRobs) that morphologically replicates the logarithmic spiral pattern observed in natural appendages (e.g., octopus arms, elephant trunks, etc.). This allows for a common design principle across different scales and a speedy and inexpensive fabrication process. We further present a grasping strategy inspired by the octopus that can automatically adapt to a target object's size and shape. We illustrate the dexterity of SpiRobs and the ability to tightly grasp objects that vary in size by more than two orders of magnitude and up to 260 times self-weight. We demonstrate scalability via three additional variants: a miniaturized gripper (mm), a one-meter-long manipulator, and an array of SpiRobs that can tangle up various objects.