Compute-Bound and Low-Bandwidth Distributed 3D Graph-SLAM

TL;DR

This paper introduces a distributed 3D SLAM map-building architecture that adapts to bandwidth and computational constraints using a novel ultra-fast 3D point cloud compression method, enabling resource-limited robots to perform effective SLAM.

Contribution

The paper presents a new adaptive 3D compression algorithm integrated with DVO SLAM, allowing resource-constrained robots to efficiently build and share 3D maps.

Findings

Compression algorithm is ultra-fast and adaptive.

Enables resource-limited platforms to perform 3D SLAM.

Improves communication efficiency for distributed mapping.

Abstract

This article describes a new approach for distributed 3D SLAM map building. The key contribution of this article is the creation of a distributed graph-SLAM map-building architecture responsive to bandwidth and computational needs of the robotic platform. Responsiveness is afforded by the integration of a 3D point cloud to plane cloud compression algorithm that approximates dense 3D point cloud using local planar patches. Compute bound platforms may restrict the computational duration of the compression algorithm and low-bandwidth platforms can restrict the size of the compression result. The backbone of the approach is an ultra-fast adaptive 3D compression algorithm that transforms swaths of 3D planar surface data into planar patches attributed with image textures. Our approach uses DVO SLAM, a leading algorithm for 3D mapping, and extends it by computationally isolating map integration tasks from local Guidance, Navigation, and Control tasks and includes an addition of a network protocol to share the compressed plane clouds. The joint effect of these contributions allows agents with 3D sensing capabilities to calculate and communicate compressed map information commensurate with their onboard computational resources and communication channel capacities. This opens SLAM mapping to new categories of robotic platforms that may have computational and memory limits that prohibit other SLAM solutions.