Skip to content

MarineRoboticsGroup/awesome-object-SLAM

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

83 Commits
 
 

Repository files navigation

Awesome Object SLAM Awesome

A curated list of Object SLAM papers and resources, inspired by awesome-implicit-representations.

Disclaimer

This list does not aim to be exhaustive. In this list, we consider papers that jointly optimize robot (camera) and object states, where object states typically include object poses and object shape parameters.

For more general SLAM papers, please refer to awesome-visual-SLAM and Awesome-SLAM.

This repo is mainitained by Ziqi Lu and Akash Sharma. You are very welcome to contribute to this repo. If you spot anything wrong or missing, please feel free to submit a pull request or contact the maintainers.

Table of Contents

What is Object SLAM?

Object SLAM, loosely speaking tackles the problem of Simultaneous Localisation and Mapping (SLAM) by building a 3D object-level global environment map from local observations. To build such a map of the environment, object detection, pose estimation and instance segmentation networks are typically used as virtual sensors in a sensor fusion framework. Representing the 3D map with objects is interesting as it is easy to ascribe semantics to the landmarks to perform higher-level tasks such as object manipulation, motion and task planning, etc. It compresses the map by focusing compute and memory for meaningful regions, and map abstraction is also useful for other tasks such as distributed map building.

Papers

Parametric Object Representation (Cubes/Quadrics/6DoF Pose/etc.)

  • 2023

    • An Object SLAM Framework for Association, Mapping, and High-Level Tasks. [PDF]
    • BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects. [PDF] [Code] [Video]
    • Object-based SLAM utilizing unambiguous pose parameters considering general symmetry types. [PDF] [Video]
  • 2022

    • LayoutSLAM: Object Layout based Simultaneous Localization and Mapping for Reducing Object Map Distortion. [PDF]
    • OA-SLAM: Leveraging Objects for Camera Relocalization in Visual SLAM. [PDF] [Code] [Video1] [Video2]
    • SO-SLAM: Semantic Object SLAM with Scale Proportional and Symmetrical Texture Constraints. [PDF] [Code]
    • SQ-SLAM: Monocular Semantic SLAM Based on Superquadric Object Representation. [PDF] [Code]
    • Symmetry and Uncertainty-Aware Object SLAM for 6DoF Object Pose Estimation. [PDF] [Code]
  • 2021

    • Accurate and Robust Object-oriented SLAM with 3D Quadric Landmark Construction in Outdoor Environment. [PDF] [Video]
    • A Multi-Hypothesis Approach to Pose Ambiguity in Object-Based SLAM. [PDF] [Video]
    • BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Models. [PDF] [Code] [Video]
    • DynaSLAM II: Tightly-Coupled Multi-Object Tracking and SLAM. [PDF]
    • Object-Augmented RGB-D SLAM for Wide-Disparity Relocalisation. [PDF] [Code] [Video]
  • 2020

  • 2019

    • CubeSLAM: Monocular 3D Object SLAM. [PDF] [Code] [Video]
    • Monocular Object and Plane SLAM in Structured Environments. [PDF] [Video]
    • QuadricSLAM: Dual Quadrics from Object Detections as Landmarks in Object-Oriented SLAM. [PDF] [Code] [Video]
    • Real-Time Monocular Object-Model Aware Sparse SLAM. [PDF] [Video]
    • Robust Object-based SLAM for High-Speed Autonomous Navigation. [PDF]
  • 2018

    • Structure Aware SLAM using Quadrics and Planes. [PDF] [Video]
  • 2016

  • 2013

    • SLAM++: Simultaneous Localisation and Mapping at the Level of Objects. [PDF] [Video]
  • 2011

    • Semantic Structure From Motion with Object and Point Interactions. [PDF]
    • Towards Semantic SLAM using a Monocular Camera. [PDF] [Video1] [Video2]
  • 2008

    • Object-based Visual SLAM: How Object Identity Informs Geometry. [PDF]

Field Object Representation (Neural Fields/Dense Grids/etc.)

Inference Methods for Object SLAM

  • 2022

  • 2021

    • Consensus-Informed Optimization Over Mixtures for Ambiguity-Aware Object SLAM. [PDF] [Video]
  • 2020

    • Probabilistic Data Association via Mixture Models for Robust Semantic SLAM. [PDF] [Video]
  • 2019

  • 2018

    • A Unifying View of Geometry, Semantics, and Data Association in SLAM. [PDF] [Video]
  • 2017

    • Probabilistic Data Association for Semantic SLAM. [PDF]
  • 2016

Reviews

  • 2021

    • Advances in Inference and Representation for Simultaneous Localization and Mapping. [PDF]
  • 2020

    • Semantics for Robotic Mapping, Perception and Interaction: A Survey. [PDF]

Resources

Datasets

About

A curated list of Object SLAM papers and resources

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published