RhoMorph: Rhombus-shaped Deformable Modular Robots for Stable, Medium-Independent Reconfiguration Motion
- URL: http://arxiv.org/abs/2601.19529v2
- Date: Thu, 19 Mar 2026 04:31:59 GMT
- Title: RhoMorph: Rhombus-shaped Deformable Modular Robots for Stable, Medium-Independent Reconfiguration Motion
- Abstract summary: RhoMorph is a deformable planar lattice modular self-reconfigurable robot (MSRR)<n>Each module consists of a parallelogram skeleton with a single centrally mounted actuator that enables folding and unfolding along its diagonal.<n>To leverage the unique kinematics of RhoMorph, we introduce morphpivoting, a novel motion primitive for reconfiguration that differs from advanced MSRR systems.
- Score: 19.07539331659169
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In this paper, we present RhoMorph, a novel deformable planar lattice modular self-reconfigurable robot (MSRR) with a rhombus shaped module. Each module consists of a parallelogram skeleton with a single centrally mounted actuator that enables folding and unfolding along its diagonal. The core design philosophy is to achieve essential MSRR functionalities such as morphing, docking, and locomotion with minimal control complexity. This enables a continuous and stable reconfiguration process that is independent of the surrounding medium, allowing the system to reliably form various configurations in diverse environments. To leverage the unique kinematics of RhoMorph, we introduce morphpivoting, a novel motion primitive for reconfiguration that differs from advanced MSRR systems, and propose a strategy for its continuous execution. Finally, a series of physical experiments validate the module's stable reconfiguration ability, as well as its positional and docking accuracy.
Related papers
- Learning Adaptive Dynamical Features via Multi-$τ$ Liquid-Mamba for All-in-one Image Restoration [53.80629284653929]
Liquid-Mamba is an adaptive state space module that introduces input adaptability of multi-timescale liquid discretization into selective state space modeling.<n>We develop a Multi$$ LiquidMamba Image Restoration Network (MLMIR) for all-in-one image restoration.
arXiv Detail & Related papers (2026-06-22T03:20:18Z) - PenduMorph: Development and Motion Analysis of Pendulum-Actuated Rolling Reconfigurable Spherical Robot with Magnetic-Coupling [9.674037525896503]
"PenduMorph" is a wireless reconfigurable rolling spherical robot designed as a modular platform for enclosed locomotion and inter- module interaction.<n>The proposed robot extends our previous pendulum-actuated rolling disk concept to a fully enclosed spherical architecture integrating a 2-DoF internal pendulum, onboard control, battery-powered operation, and magnetic docking.
arXiv Detail & Related papers (2026-06-21T13:24:52Z) - Reinforcement learning in linear embedding space unlocks generalizable control across soft robot configurations [60.42735420750131]
Soft-bodied organisms such as octopuses and elephant trunks exhibit remarkable morphological adaptability.<n>Various soft robots have emerged in recent decades, featuring diverse materials, stiffnesses, and morphologies tailored to specific tasks.<n>Here, we introduce a generalizable control system that enables rapid adaptation across diverse soft robot configurations.
arXiv Detail & Related papers (2026-06-06T11:09:46Z) - ZipFold: Modular Actuators for Scaleable Adaptive Robots [52.52738470247707]
This paper introduces a compact, easy-to-fabricate deployable actuator that achieves reversible scale and stiffness transformations.<n>The simple actuation method allows for smooth, continuous transitions between compact (flexible) and expanded (quasi-rigid) states.
arXiv Detail & Related papers (2026-04-06T23:50:03Z) - From Folding Mechanics to Robotic Function: A Unified Modeling Framework for Compliant Origami [13.163657221687599]
We introduce a geometry consistent modeling framework based on discrete differential geometry (DDG)<n>This framework unifies panel elasticity and crease rotation within a single variational formulation.<n>This unified description enables programmable control of stability and deformation across rigid and compliant regimes.
arXiv Detail & Related papers (2026-03-16T07:03:39Z) - Design and Control of Modular Magnetic Millirobots for Multimodal Locomotion and Shape Reconfiguration [5.7788762754943654]
We present a modular magnetic millirobotic platform for on-demand assembly and disassembly.<n>A free module supports self-assembly and reconfiguration, a fixed module enables flip-and-walk locomotion, and a gripper module for cargo manipulation.<n>The system achieves self-assembly, multimodal transformations, and disassembly at low field strengths.
arXiv Detail & Related papers (2026-02-22T21:25:05Z) - Morphogenetic Assembly and Adaptive Control for Heterogeneous Modular Robots [9.732115880925306]
This paper presents a closed-loop automation framework for heterogeneous modular robots.<n>A mobile manipulator handles heterogeneous functional modules to dynamically assemble diverse robot configurations.<n>The framework validates the full-cycle process, including module assembly, robot merging and splitting, and dynamic motion generation.
arXiv Detail & Related papers (2026-02-11T06:18:04Z) - Self-Reconfiguration Planning for Deformable Quadrilateral Modular Robots [9.249285433601205]
lattice modular self-reconfigurable robots (MSRRs)<n>Maintaining stable connections during reconfiguration is crucial for physical feasibility and deployability.<n>This letter presents a novel self-reconfiguration planning algorithm for deformable quadrilateral MSRRs that guarantees stable connection.
arXiv Detail & Related papers (2026-01-27T11:32:04Z) - A Rotation-Invariant Embedded Platform for (Neural) Cellular Automata [25.31070593685097]
This paper presents a rotation-invariant embedded platform for simulating (neural) cellular automata (NCA) in modular robotic systems.<n>Inspired by previous work on physical NCA, we introduce key innovations that overcome limitations in prior hardware designs.<n>Our platform features a symmetric, modular structure, enabling seamless connections between cells regardless of orientation.
arXiv Detail & Related papers (2025-10-08T18:39:14Z) - Learning Modulated Transformation in GANs [69.95217723100413]
We equip the generator in generative adversarial networks (GANs) with a plug-and-play module, termed as modulated transformation module (MTM)
MTM predicts spatial offsets under the control of latent codes, based on which the convolution operation can be applied at variable locations.
It is noteworthy that towards human generation on the challenging TaiChi dataset, we improve the FID of StyleGAN3 from 21.36 to 13.60, demonstrating the efficacy of learning modulated geometry transformation.
arXiv Detail & Related papers (2023-08-29T17:51:22Z) - SceNeRFlow: Time-Consistent Reconstruction of General Dynamic Scenes [75.9110646062442]
We propose SceNeRFlow to reconstruct a general, non-rigid scene in a time-consistent manner.
Our method takes multi-view RGB videos and background images from static cameras with known camera parameters as input.
We show experimentally that, unlike prior work that only handles small motion, our method enables the reconstruction of studio-scale motions.
arXiv Detail & Related papers (2023-08-16T09:50:35Z) - Squeezeformer: An Efficient Transformer for Automatic Speech Recognition [99.349598600887]
Conformer is the de facto backbone model for various downstream speech tasks based on its hybrid attention-convolution architecture.
We propose the Squeezeformer model, which consistently outperforms the state-of-the-art ASR models under the same training schemes.
arXiv Detail & Related papers (2022-06-02T06:06:29Z) - Co-evolution of Functional Brain Network at Multiple Scales during Early
Infancy [52.4179778122852]
This paper leveraged a longitudinal infant resting-state functional magnetic resonance imaging dataset from birth to 2 years of age.
By applying our proposed methodological framework on the collected longitudinal infant dataset, we provided the first evidence that, in the first 2 years of life, the brain functional network is co-evolved at different scales.
arXiv Detail & Related papers (2020-09-15T07:21:04Z) - S2RMs: Spatially Structured Recurrent Modules [105.0377129434636]
We take a step towards exploiting dynamic structure that are capable of simultaneously exploiting both modular andtemporal structures.
We find our models to be robust to the number of available views and better capable of generalization to novel tasks without additional training.
arXiv Detail & Related papers (2020-07-13T17:44:30Z) - Euclideanizing Flows: Diffeomorphic Reduction for Learning Stable
Dynamical Systems [74.80320120264459]
We present an approach to learn such motions from a limited number of human demonstrations.
The complex motions are encoded as rollouts of a stable dynamical system.
The efficacy of this approach is demonstrated through validation on an established benchmark as well demonstrations collected on a real-world robotic system.
arXiv Detail & Related papers (2020-05-27T03:51:57Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.