Mae Seto

About

Mae Seto is a prominent robotics researcher whose work spans multi-robot systems, autonomous underwater vehicles (AUVs), and simultaneous localization and mapping (SLAM). She is perhaps best known for her highly cited 2015 review of multiple-robot SLAM (322 citations), which became a foundational reference for researchers tackling localization in GPS-denied environments. Her subsequent work on communication-constrained multi-AUV cooperative SLAM (108 citations) extended these ideas into the challenging domain of underwater robotics, where bandwidth limitations make coordination particularly demanding. Beyond SLAM, Seto has made meaningful contributions to quadrotor control and navigation (103 citations), neural-network-based path planning for multi-robot systems (90 citations), and probabilistic area coverage for autonomous seabed mapping. Her efforts in ontology development for autonomous robots reflect a broader commitment to standardizing knowledge representation across the field. More recently, her work on heterogeneous marine robot collaboration demonstrates an evolving focus on real-world maritime applications, including inspection of unresponsive floating targets. With over 800 cumulative citations across her most recognized publications, Seto's research has significantly shaped the theoretical and practical foundations of autonomous multi-robot systems, particularly in challenging, communication-constrained marine environments.

Research Focus

Key Achievements

Top Papers

1. 1
   Multiple-Robot Simultaneous Localization and Mapping: A Review

   322 citations · 2015
2. 2
   Communication-constrained multi-AUV cooperative SLAM

   108 citations · 2015
3. 3
   Control and Navigation Framework for Quadrotor Helicopters

   103 citations · 2012
4. 4
   Neural-Network-Based Path Planning for a Multirobot System With Moving Obstacles

   90 citations · 2009
5. 5
   Group Mapping: A Topological Approach to Map Merging for Multiple Robots

   57 citations · 2014
6. 6
   Requirements for building an ontology for autonomous robots

   44 citations · 2016
7. 7
   Towards an Ontology for Autonomous Robots

   38 citations · 2012
8. 8
   Probabilistic cooperative mobile robot area coverage and its application to autonomous seabed mapping

   37 citations · 2017
9. 9
   Map merging for multiple robots using Hough peak matching

   36 citations · 2014
10. 10
    Collaboration of Heterogeneous Marine Robots Toward Multidomain Sensing and Situational Awareness on Partially Submerged Targets

    29 citations · 2022

Key Collaborators

Contact & Links