DS-K3DOM: 3-D Dynamic Occupancy Mapping with Kernel Inference and Dempster-Shafer Evidential Theory-Reference-Cited by-同舟云学术

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DS-K3DOM: 3-D Dynamic Occupancy Mapping with Kernel Inference and Dempster-Shafer Evidential Theory

Published:2023-05-29 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Robotics and Automation (ICRA)
language:
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Author:

Han Juyeop¹,Min Youngjae²,Chae Hyeok-Joo¹,Jeong Byeong-Min¹,Choi Han-Lim¹

Affiliation:

1. KAIST Institutes for Robotics, Korea Advanced Institide of Science and Technology (KAIST),Department of Aerospace Engineering,Daejeon,South Korea,34141

2. Massachusetts Institute of Technology,Laboratory for Information and Decision Systems (LIDS),Cambridge,MA,USA,02139

Funder

National Research Foundation of Korea(NRF)

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10160211/10160212/10160364.pdf?arnumber=10160364

Reference18 articles.

1. Interpreting Belief Functions as Dirichlet Distributions

2. Kernel-Based 3-D Dynamic Occupancy Mapping with Particle Tracking

3. An overview of particle methods for random finite set models

4. A random finite set approach for dynamic occupancy grid maps with real-time application

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