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Updated: Dec 19, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy

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Published on: October 14, 2017

Optimization Complete Area Coverage by Reconfigurable hTrihex Tiling Robot.

Anh Vu Le^1,2, Rizuwana Parween¹, Rajesh Elara Mohan¹

¹ROAR Lab, Engineering Product Development, Singapore University of Technology and Design, Singapore 487372, Singapore.

Sensors (Basel, Switzerland)

|June 7, 2020

Summary

This summary is machine-generated.

This study introduces a novel framework for shape-changing tiling robots to achieve complete area coverage planning. The developed algorithm optimizes robot navigation for efficiency and adaptability in diverse environments.

Keywords:

complete coverage energy optimization path planning shapeshifting robot tiling robotic

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Last Updated: Dec 19, 2025

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Area of Science:

Robotics and Automation
Computational Geometry
Artificial Intelligence

Background:

Completed area coverage planning (CACP) is crucial for robotic applications like exploration and maintenance.
Tiling robots with adaptable shapes offer enhanced coverage flexibility and access to confined spaces.

Purpose of the Study:

To develop a CACP framework for a shape-shifting tiling robot (hTrihex) to optimize navigation.
To address challenges in minimizing shape changes, travel distance, and time while ensuring full area coverage.

Main Methods:

A novel CACP framework for the hTrihex robot with three honeycomb modules.
Modeling trajectory optimization as a Traveling Salesman Problem (TSP).
Solving the TSP using Genetic Algorithm (GA) and Ant Colony Optimization (ACO), considering transformation, translation, and orientation energy costs.

Main Results:

The proposed CACP framework successfully generated Pareto-optimal navigation solutions.
The hTrihex robot demonstrated efficient coverage in both simulated and real-world environments.
The framework proved effective in various workspaces with different robot configurations.

Conclusions:

The CACP framework enables efficient and adaptable area coverage for shape-changing robots.
The algorithm's adaptability allows for potential adoption by other multi-configuration tiling robot platforms.
This research advances robotic capabilities in complex area coverage tasks.