Reconfiguration-Complete Motion Primitives with Constructive Planning for Deformable Planar Modular Robots

📅 2026-08-17
📈 Citations: 0
Influential: 0
📄 PDF
🤖 AI Summary
研究解决了变形平面模块化机器人重构规划问题,通过引入方形单元抽象和两种基本运动(旋转和剪切),并证明了所有非直线连接配置均可转换为标准阶梯形。
📝 Abstract
The continuously deformable geometry of modular robots makes it difficult to define a fixed representation for reconfiguration planning and analysis. This letter introduces a square-cell abstraction that maps deformable rhombus modules to fixed-size grid cells while retaining physically interpretable local motions through two primitives, pivoting and shearing. Under this abstraction, we prove that every non-straight edge-connected configuration with $N \geq 7$ can be transformed to a fixed canonical staircase using only admissible primitive motions. Since these motions are reversible, any two configurations in this class are mutually reconfigurable. The proof is constructive and directly yields a staircase-canonicalization planner that transports removable boundary modules while preserving connectivity. As a practical enhancement, we further introduce a boundary-to-delivery lookahead selector that ranks admissible high level choices without affecting the completeness guarantee. Experiments demonstrate the constructive reconfiguration process and show that the selector substantially reduces planning time, while reference comparisons indicate lower planning times than the prior framework over the shared module counts.
Problem

Research questions and friction points this paper is trying to address.

deformable planar modular robots
reconfiguration planning
fixed representation
Innovation

Methods, ideas, or system contributions that make the work stand out.

square-cell abstraction
pivoting and shearing primitives
staircase-canonicalization planner
boundary-to-delivery lookahead selector
🔎 Similar Papers
No similar papers found.
💼 Related Jobs
No related jobs found.
Jie Gu
Jie Gu
Professor of Electrical Engineering and Computer Science, Northwestern University
VLSI DesignMixed-signal DesignEmerging Technology IntegrationComputer Architecture
T
Tingting Wang
Institute of AI and Robotics, Academy for Engineering & Technology, Fudan University, Shanghai 200433, China
H
Hongrun Gao
Institute of AI and Robotics, Academy for Engineering & Technology, Fudan University, Shanghai 200433, China
Y
Yirun Sun
Institute of AI and Robotics, Academy for Engineering & Technology, Fudan University, Shanghai 200433, China
Z
Zhihao Xia
Institute of AI and Robotics, Academy for Engineering & Technology, Fudan University, Shanghai 200433, China
C
Chunxu Tian
Institute of AI and Robotics, Academy for Engineering & Technology, Fudan University, Shanghai 200433, China
D
Dan Zhang
Department of Mechanical Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China