Multiple‐Robot Simultaneous Localization and Mapping: A Review
By Sajad Saeedi, Michael Trentini, Mae L. Seto, Howard Li. J. Field Robotics, 2016
313 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Electrical and Electronic Engineering, Ocean Engineering
View Paper: https://www.semanticscholar.org/paper/7e2224d742e1addb09b1042623a1385122b8f64e
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- Shaojie Shen
- Yun Chang
- Sunwook Choi
- Giseop Kim
- Vijay R. Kumar
- Ayoung Kim
- Khaled Ben Letaief
- Luca Carlone
In Electrical and Electronic Engineering
- Khaled Ben Letaief
- Jun Zhang
- Luca Carlone
- Yun Chang
- Zsolt Kira
- Jonathan P. How
- Soon-Jo Chung
- Shaojie Shen
In Ocean Engineering
- Shaojie Shen
- Khaled Ben Letaief
- Zsolt Kira
- Yen-Cheng Liu
- Soon-Jo Chung
- Sunwook Choi
- Jun Zhang
- Vijay R. Kumar
Citations in the corpus
- Kimera-Multi: Robust, Distributed, Dense Metric-Semantic SLAM for Multi-Robot Systems (2021, background): “, occupancy maps [32]) or sparse landmark maps [6, 33]; see [34] and the references therein.”
- Mobile Edge Intelligence and Computing for the Internet of Vehicles (2019, methodology): “Besides edge-assisted centralized SLAM mentioned in the previous subsection, decentralized SLAM has also been proposed, where each vehicle builds its own decentralized map while communicating with the other vehicles [150].”
- Who2com: Collaborative Perception via Learnable Handshake Communication (2020, background): “Unlike past methods that focus on multi-robot localization and mapping [6, 32], we develop agents that learn what to communicate in a manner that is amenable to end-to-end deep learning, which dominates scene understanding.”
- Scan Context++: Structural Place Recognition Robust to Rotation and Lateral Variations in Urban Environments (2021, background): “Recognizing a previously visited place is important for various robot missions (e.g., loop detection in simultaneous localization and mapping (SLAM) [1], global localization for a kidnapped robot [2], or multi-robot mapping [3]).”
- A Survey on Aerial Swarm Robotics (2018, background): “Further discussion of these technical challenges follows in Section V. Problems and current solutions for multirobot mapping are reviewed in [188].”
- Simultaneous Localization and Mapping: A Survey of Current Trends in Autonomous Driving (2017, unknown): “Finally, in [94], the authors review multiple-robot SLAM approaches with a description of the underlying mathematical formulation.”
- Past, Present, and Future of Simultaneous Localization and Mapping: Toward the Robust-Perception Age (2016, unknown): “A recent survey on multirobot SLAM approaches can be found in [216].”