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autox-semmap repository

robotics navigation exploration object-detection semantic-mapping object-segmentation autonomous-navigation
Repo symbol

autox-semmap repository

robotics navigation exploration object-detection semantic-mapping object-segmentation autonomous-navigation
Repo symbol

autox-semmap repository

robotics navigation exploration object-detection semantic-mapping object-segmentation autonomous-navigation
Repo symbol

autox-semmap repository

robotics navigation exploration object-detection semantic-mapping object-segmentation autonomous-navigation

Repository Summary

Description Autonomous Exploration, Construction and Update of Semantic Map in real-time
Checkout URI https://github.com/irvlutd/autox-semmap.git
VCS Type git
VCS Version main
Last Updated 2025-05-29
Dev Status UNKNOWN
Released UNRELEASED
Tags robotics navigation exploration object-detection semantic-mapping object-segmentation autonomous-navigation
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

README

Autonomous Exploration and Semantic Updating of Large-Scale Indoor Environments with Mobile Robots​​

Sai Haneesh Allu, Itay Kadosh, Tyler Summers, Yu Xiang

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arXiv ** ** Project WebPage ** ** Video

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We introduce a new robotic system that enables a mobile robot to autonomously explore an unknown environment, build a semantic map of the environment, and subsequently update the semantic map to reflect environment changes, such as location changes of objects. Our system leverages a LiDAR scanner for 2D occupancy grid mapping and an RGB-D camera for object perception. We introduce a semantic map representation that combines a 2D occupancy grid map for geometry with a topological map for object semantics. This map representation enables us to effectively update the semantics by deleting or adding nodes to the topological map. Our system has been tested on a Fetch robot, semantically mapping a 93m x 90m and a 9m x 13m indoor environment and updating their semantic maps once objects are moved in the environments



image info


Citation

Please cite this work if it helps in your research

@inproceedings{allu2024semanticmapping,
      title={Autonomous Exploration and Semantic Updating of Large-Scale Indoor Environments with Mobile Robots},
      author={Allu, Sai Haneesh and Kadosh, Itay and Summers, Tyler and Xiang, Yu},
      journal={arXiv preprint arXiv:2409.15493},
      year={2024}
    }

For any questions regarding this work, contact Sai Haneesh Allu. For any issues regarding this code, please raise an issue.

Index

  1. Installation
  2. Initialization
  3. Mapping and Exploration
  4. Environment Traversal planning
  5. Semantic Map Construction and Update
  6. Running on a real robot system
  7. Real World Demo



Installation

The following subsections provides detailed installation guidelines related to workspace setup, dependencies and other requirements to test this work effectively. Additionally, a docker has been provided with instructions. Credits to Iminolee .

A. Install ROS and Gazebo

This code is tested on ros noetic version. Detailed installation instructions are found here.To install ROS Noetic, execute the following commands in your terminal:

sudo sh -c 'echo "deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main" > /etc/apt/sources.list.d/ros-latest.list'

sudo apt install -y curl

curl -s https://raw.githubusercontent.com/ros/rosdistro/master/ros.asc | sudo apt-key add -

sudo apt update

sudo apt install -y ros-noetic-desktop-full

echo "source /opt/ros/noetic/setup.bash" >> ~/.bashrc

source ~/.bashrc

For compatibility with ROS Noetic, Gazebo 11 is recommended. Detailed installation instructions are found here.

sudo sh -c 'echo "deb http://packages.osrfoundation.org/gazebo/ubuntu-stable `lsb_release -cs` main" > /etc/apt/sources.list.d/gazebo-stable.list'

wget https://packages.osrfoundation.org/gazebo.key -O - | sudo apt-key add -

sudo apt-get update

sudo apt-get install -y gazebo11

B. Create Conda Environment

We strongly recommend using a virtual environment for this work, preferably Anaconda or Miniconda. Create a new environment as follows:

conda create -n sem-map python==3.9
conda activate sem-map

C. Clone the repository

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Repo symbol

autox-semmap repository

robotics navigation exploration object-detection semantic-mapping object-segmentation autonomous-navigation
Repo symbol

autox-semmap repository

robotics navigation exploration object-detection semantic-mapping object-segmentation autonomous-navigation
Repo symbol

autox-semmap repository

robotics navigation exploration object-detection semantic-mapping object-segmentation autonomous-navigation
Repo symbol

autox-semmap repository

robotics navigation exploration object-detection semantic-mapping object-segmentation autonomous-navigation