Efficient Factor Graph Fusion for Multi-Robot Mapping and Beyond

Natarajan, Ramkumar; Gennert, Michael A.

doi:10.23919/icif.2018.8455502

Cited by 5 publications

(1 citation statement)

References 24 publications

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“…The algorithms for multi-robot SLAM tend to be extensions of the single robot SLAM algorithms described above in section IV, such as filtering methods based on the EKF [275], the extended information filter [276], [277], and the particle filter [278], and smoothing/optimization methods based on GraphSLAM [279], SAM [280], [281] and iSAM2 [282]. There are also a number of works that specifically address multi-robot visual SLAM using both centralised [283], [284] and decentralised/distributed fusion [285], [286], where the approach in [284] specifically targets the use of the cloud to perform centralised processing for the computationally intensive map optimization and data storage -an appealing approach for low-powered robots in pipes.…”

Section: Multi-robot Slam In Water and Sewer Pipesmentioning

confidence: 99%

Simultaneous Localization and Mapping for Inspection Robots in Water and Sewer Pipe Networks: A Review

et al. 2021

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At the present time, water and sewer pipe networks are predominantly inspected manually. In the near future, smart cities will perform intelligent autonomous monitoring of buried pipe networks, using teams of small robots. These robots, equipped with all necessary computational facilities and sensors (optical, acoustic, inertial, thermal, pressure and others) will be able to inspect pipes whilst navigating, selflocalising and communicating information about the pipe condition and faults such as leaks or blockages to human operators for monitoring and decision support. The predominantly manual inspection of pipe networks will be replaced with teams of autonomous inspection robots that can operate for long periods of time over a large spatial scale. Reliable autonomous navigation and reporting of faults at this scale requires effective localization and mapping, which is the estimation of the robot's position and its surrounding environment. This survey presents an overview of state-of-the-art works on robot simultaneous localization and mapping (SLAM) with a focus on water and sewer pipe networks. It considers various aspects of the SLAM problem in pipes, from the motivation, to the water industry requirements, modern SLAM methods, map-types and sensors suited to pipes. Future challenges such as robustness for long term robot operation in pipes are discussed, including how making use of prior knowledge, e.g. geographic information systems (GIS) can be used to build map estimates, and improve the multi-robot SLAM in the pipe environment.

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