Sajad Saeedi

About

Sajad Saeedi is a prominent robotics researcher whose work spans autonomous navigation, simultaneous localization and mapping (SLAM), and aerial robotics. Best known for his highly influential 2015 review on Multiple-Robot SLAM (322 citations), Saeedi has made foundational contributions to solving one of mobile robotics' most persistent challenges: enabling teams of robots to collaboratively map and navigate GPS-denied environments. His early work on neural network-based multi-robot SLAM and topological map merging techniques helped establish practical frameworks that researchers continue to build upon today. Beyond multi-robot systems, Saeedi has broadened his research portfolio impressively. His contributions to quadrotor control and navigation, UAV package delivery, and UV disinfection robotics demonstrate a versatile approach to autonomous systems with real-world applications. His involvement in the IEEE Ontologies for Robotics and Automation Working Group and his contributions to the SLAMBench evaluation framework reflect a commitment to standardization and reproducibility in the field. With over 700 cumulative citations across his most impactful papers, Saeedi's work represents a significant body of knowledge for students and researchers seeking to understand both the theoretical underpinnings and practical deployment of autonomous robotic systems.

Research Focus

Key Achievements

Top Papers

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

   322 citations · 2015
2. 2
   Control and Navigation Framework for Quadrotor Helicopters

   103 citations · 2012
3. 3
   UV Disinfection Robots: A Review

   76 citations · 2022
4. 4
   Autonomous aerial robotics for package delivery: A technical review

   72 citations · 2023
5. 5
   Neural Network-Based Multiple Robot Simultaneous Localization and Mapping

   66 citations · 2011
6. 6
   Group Mapping: A Topological Approach to Map Merging for Multiple Robots

   57 citations · 2014
7. 7
   Navigating the Landscape for Real-Time Localization and Mapping for Robotics and Virtual and Augmented Reality

   51 citations · 2018
8. 8
   Requirements for building an ontology for autonomous robots

   44 citations · 2016
9. 9
   SLAMBench 3.0: Systematic Automated Reproducible Evaluation of SLAM Systems for Robot Vision Challenges and Scene Understanding

   37 citations · 2019
10. 10
    Map merging for multiple robots using Hough peak matching

    36 citations · 2014

Key Collaborators

Contact & Links