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Bibliographic Details
Main Authors: Asgharivaskasi, Arash, Atanasov, Nikolay
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2402.08867
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author Asgharivaskasi, Arash
Atanasov, Nikolay
author_facet Asgharivaskasi, Arash
Atanasov, Nikolay
contents This work develops a distributed optimization algorithm for multi-robot 3-D semantic mapping using streaming range and visual observations and single-hop communication. Our approach relies on gradient-based optimization of the observation log-likelihood of each robot subject to a map consensus constraint to build a common multi-class map of the environment. This formulation leads to closed-form updates which resemble Bayes rule with one-hop prior averaging. To reduce the amount of information exchanged among the robots, we utilize an octree data structure that compresses the multi-class map distribution using adaptive-resolution.
format Preprint
id arxiv_https___arxiv_org_abs_2402_08867
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Distributed Optimization with Consensus Constraint for Multi-Robot Semantic Octree Mapping
Asgharivaskasi, Arash
Atanasov, Nikolay
Robotics
This work develops a distributed optimization algorithm for multi-robot 3-D semantic mapping using streaming range and visual observations and single-hop communication. Our approach relies on gradient-based optimization of the observation log-likelihood of each robot subject to a map consensus constraint to build a common multi-class map of the environment. This formulation leads to closed-form updates which resemble Bayes rule with one-hop prior averaging. To reduce the amount of information exchanged among the robots, we utilize an octree data structure that compresses the multi-class map distribution using adaptive-resolution.
title Distributed Optimization with Consensus Constraint for Multi-Robot Semantic Octree Mapping
topic Robotics
url https://arxiv.org/abs/2402.08867