Emergent functional dynamics of link-bots
November 12, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Kyungmin Son, Kimberly Bowal, L. Mahadevan, Ho-Young Kim
arXiv ID
2411.08163
Category
cond-mat.soft
Cross-listed
cs.RO
Citations
0
Venue
arXiv.org
Last Checked
3 months ago
Abstract
Synthetic active collectives, composed of many nonliving individuals capable of cooperative changes in group shape and dynamics, hold promise for practical applications and for the elucidation of guiding principles of natural collectives. However, the design of collective robotic systems that operate effectively without intelligence or complex control at either the individual or group level is challenging. We investigate how simple steric interaction constraints between active individuals produce a versatile active system with promising functionality. Here we introduce the link-bot: a V-shape-based, single-stranded chain composed of active bots whose dynamics are defined by its geometric link constraints, allowing it to possess scale- and processing-free programmable collective behaviors. A variety of emergent properties arise from this dynamic system, including locomotion, navigation, transportation, and competitive or cooperative interactions. Through the control of a few link parameters, link-bots show rich usefulness by performing a variety of divergent tasks, including traversing or obstructing narrow spaces, passing by or enclosing objects, and propelling loads in both forward and backward directions. The reconfigurable nature of the link-bot suggests that our approach may significantly contribute to the development of programmable soft robotic systems with minimal information and materials at any scale.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β cond-mat.soft
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Programming Soft Robots with Flexible Mechanical Metamaterials
R.I.P.
π»
Ghosted
Polymers for Extreme Conditions Designed Using Syntax-Directed Variational Autoencoders
R.I.P.
π»
Ghosted
Machine learning enables polymer cloud-point engineering via inverse design
R.I.P.
π»
Ghosted
Programming Active Cohesive Granular Matter with Mechanically Induced Phase Changes
R.I.P.
π»
Ghosted
Understanding Legged Crawling for Soft-Robotics
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted