Multi-Robot Multi-Room Exploration with Geometric Cue Extraction and Circular Decomposition - Robotics Institute Carnegie Mellon University

Multi-Robot Multi-Room Exploration with Geometric Cue Extraction and Circular Decomposition

Seungchan Kim, Micah Corah, John Keller, Graeme Best, and Sebastian Scherer
Journal Article, IEEE Robotics and Automation Letters, December, 2023

Abstract

This work proposes an autonomous multi-robot exploration pipeline that coordinates the behaviors of robots in an indoor environment composed of multiple rooms. Contrary to simple frontier-based exploration approaches, we aim to enable robots to methodically explore and observe an unknown set of rooms in a structured building, keeping track of which rooms are already explored and sharing this information among robots to coordinate their behaviors in a distributed manner. To this end, we propose (1) a geometric cue extraction method that processes 3D point cloud data and detects the locations of potential cues such as doors and rooms, (2) a circular decomposition for free spaces used for target assignment. Using these two components, our pipeline effectively assigns tasks among robots, and enables a methodical exploration of rooms. We evaluate the performance of our pipeline using a team of up to 3 aerial robots, and show that our method outperforms the baseline by 33.4% in simulation and 26.4% in real-world experiments.

BibTeX

@article{Kim-2023-139130,
author = {Seungchan Kim and Micah Corah and John Keller and Graeme Best and Sebastian Scherer},
title = {Multi-Robot Multi-Room Exploration with Geometric Cue Extraction and Circular Decomposition},
journal = {IEEE Robotics and Automation Letters},
year = {2023},
month = {December},
keywords = {Aerial Systems: Perception and Autonomy, Multi-Robot Systems, Vision-Based Navigation},
}