ORB-SLAM3 & RTAB-Map
ORB-SLAM3 (visual SLAM, widely used)
ORB-SLAM3 (Campos et al., 2020) is a widely used open-source visual SLAM system: it tracks the camera (or camera rig), estimates egomotion, and builds a sparse 3D map from ORB feature tracks. It supports monocular, stereo, and RGB-D input, and includes loop closing and multi-map handling.
Why it’s relevant for Konnex: the SLAM 3D map subnet is about mesh / geometry / semantics and verifiable sensor data. A miner can run ORB-SLAM3 (or a derivative) to produce trajectories, keyframe poses, and 3D landmarks for validators to compare against ground truth or scoring rules, alongside the Proof-of-Physical-Work bundle.
Paper
ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM — arXiv:2007.11898
Outputs: keyframe poses, MapPoints (sparse 3D), trajectory. A dense mesh usually needs an extra fusion step (TSDF, Poisson, etc.) on top of depth or MVS, depending on your pipeline.
Hardware: runs on CPU; GPU use depends on the build. Visual-inertial modes expect a calibrated IMU in the stack per upstream documentation.
RTAB-Map (dense 3D maps, popular in ROS)
RTAB-Map is a common choice in ROS / ROS2 when teams want online mapping with loop closure and export to occupancy grids, point clouds, or meshes for navigation and inspection. It is often a practical complement to “research” VSLAM stacks: more turnkey for room-scale RGB-D / stereo (and many LiDAR–RGB setups) in integration tutorials.
Picking a stack: use ORB-SLAM3 as a reference VIO/VSLAM baseline; use RTAB-Map when you need out-of-the-box mapping exports in a ROS-centric 3D mapping workflow.
Konnex alignment
Miners deliver reconstructions, trajectories, and signed sensor payloads as the subnet contract specifies.
Validators check fidelity and consistency (geometry, semantics, or both) per subnet design.
See also
PI-0 (manipulation) — different modality, same “miner–validator” idea
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