Continuous Occupancy Mapping in Dynamic Environments Using Particles

Gang Chen, Wei Dong, Peng Peng, Javier Alonso-Mora, Xiangyang Zhu

Research output: Contribution to journalArticleScientificpeer-review


Particle-based dynamic occupancy maps were proposed in recent years to model the obstacles in dynamic environments. Current particle-based maps describe the occupancy status in discrete grid form and suffer from the grid size problem, wherein a large grid size is unfavorable for motion planning while a small grid size lowers efficiency and causes gaps and inconsistencies. To tackle this problem, this paper generalizes the particle-based map into continuous space and builds an efficient 3D egocentric local map. A dual-structure subspace division paradigm, composed of a voxel subspace division and a novel pyramid-like subspace division, is proposed to propagate particles and update the map efficiently with the consideration of occlusions. The occupancy status at an arbitrary point in the map space can then be estimated with the weights of the particles. To reduce the noise in modeling static and dynamic obstacles simultaneously, an initial velocity estimation approach and a mixture model are utilized. Experimental results show that our map can effectively and efficiently model both dynamic obstacles and static obstacles. Compared to the state-of-the-art grid-form particle-based map, our map enables continuous occupancy estimation and substantially improves the mapping performance at different resolutions.

Original languageEnglish
Pages (from-to)64-84
Number of pages21
JournalIEEE Transactions on Robotics
Publication statusPublished - 2023

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • Aerial systems
  • collision avoidance
  • Computational modeling
  • dynamic environment
  • Kernel
  • mapping
  • Mixture models
  • perception and autonomy
  • Point cloud compression
  • Radio frequency
  • Robots
  • Three-dimensional displays


Dive into the research topics of 'Continuous Occupancy Mapping in Dynamic Environments Using Particles'. Together they form a unique fingerprint.

Cite this