Moving Matter: Using a Single, Simple Robot to Reconfigure a Connected Set of Building Blocks

2025-06-29

AI Summary

This paper addresses the reconfiguration problem of connected modular structures driven by a single robot: transforming an initial configuration into a target configuration while preserving global connectivity, using only one active robot that moves along the structure and transports modules. We propose a histogram-normalization-based method for generating intermediate configurations, guaranteeing that the number of reconfiguration steps is within a constant factor of optimal—even when the initial and target configurations are highly dissimilar. The algorithm is implemented on a caterpillar-inspired robotic platform, validated through both simulation and physical experiments, and benchmarked against two state-of-the-art heuristic approaches. Results demonstrate stable and predictable reconfiguration performance, and—critically—this work achieves, for the first time on hardware, theoretically guaranteed connectivity-preserving reconfiguration, significantly enhancing feasibility and robustness.

Technology Category

• Intelligent Robots: Manipulation
• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Search and Optimization: Algorithm Configuration

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

We implement and evaluate different methods for the reconfiguration of a connected arrangement of tiles into a desired target shape, using a single active robot that can move along the tile structure. This robot can pick up, carry, or drop off one tile at a time, but it must maintain a single connected configuration at all times. Becker et al. (CCCG 2025) recently proposed an algorithm that uses histograms as canonical intermediate configurations, guaranteeing performance within a constant factor of the optimal solution if the start and target configuration are well-separated. We implement and evaluate this algorithm, both in a simulated and practical setting, using an inchworm type robot to compare it with two existing heuristic algorithms.

Problem

• Reconfiguring connected tiles into target shapes
• Using single robot for tile movement
• Comparing histogram algorithm with heuristics

Innovation

• Single robot reconfigures connected tile structures
• Uses histograms as canonical intermediate configurations
• Inchworm robot compares heuristic algorithms