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We consider the following problem: a team of robots is deployed in an unknown environment and it has to collaboratively build a map of the area without a reliable infrastructure for communication. The backbone for modern mapping techniques…

Purpose of Review Planning collision-free paths for multiple robots is important for real-world multi-robot systems and has been studied as an optimization problem on graphs, called Multi-Agent Path Finding (MAPF). This review surveys…

Robotics · Computer Science 2022-06-24 Hang Ma

Mapping and navigation have gone hand-in-hand since long before robots existed. Maps are a key form of communication, allowing someone who has never been somewhere to nonetheless navigate that area successfully. In the context of…

Robotics · Computer Science 2024-07-16 Ian D. Miller , Fernando Cladera , Trey Smith , Camillo Jose Taylor , Vijay Kumar

Multi-robot systems such as swarms of aerial robots are naturally suited to offer additional flexibility, resilience, and robustness in several tasks compared to a single robot by enabling cooperation among the agents. To enhance the…

Robotics · Computer Science 2022-01-25 Yang Zhou , Jiuhong Xiao , Yue Zhou , Giuseppe Loianno

Exploration is a fundamental problem in robot autonomy. A major limitation, however, is that during exploration robots oftentimes have to rely on on-board systems alone for state estimation, accumulating significant drift over time in large…

Robotics · Computer Science 2021-04-15 Lukas Schmid , Victor Reijgwart , Lionel Ott , Juan Nieto , Roland Siegwart , Cesar Cadena

Multi-robot simultaneous localization and mapping (SLAM) enables a robot team to achieve coordinated tasks by relying on a common map of the environment. Constructing a map by centralized processing of the robot observations is undesirable…

Robotics · Computer Science 2024-08-22 Hanwen Cao , Sriram Shreedharan , Nikolay Atanasov

Collaborative localization is an essential capability for a team of robots such as connected vehicles to collaboratively estimate object locations from multiple perspectives with reliant cooperation. To enable collaborative localization,…

Robotics · Computer Science 2021-11-09 Peng Gao , Brian Reily , Rui Guo , Hongsheng Lu , Qingzhao Zhu , Hao Zhang

An optimization problem is at the heart of many robotics estimating, planning, and optimum control problems. Several attempts have been made at model-based multi-robot localization, and few have formulated the multi-robot collaborative…

Robotics · Computer Science 2022-10-05 Ehsan Latif , Ramviyas Parasuraman

This article presents a 3D point cloud map-merging framework for egocentric heterogeneous multi-robot exploration, based on overlap detection and alignment, that is independent of a manual initial guess or prior knowledge of the robots'…

We consider the problem of classifying a map using a team of communicating robots. It is assumed that all robots have localized visual sensing capabilities and can exchange their information with neighboring robots. Using a graph…

Robotics · Computer Science 2021-03-11 Guangyi Liu , Arash Amini , Martin Takáč , Héctor Muñoz-Avila , Nader Motee

Exploration in unknown and unstructured environments is a pivotal requirement for robotic applications. A robot's exploration behavior can be inherently affected by the performance of its Simultaneous Localization and Mapping (SLAM)…

Robotics · Computer Science 2024-09-04 Rongge Zhang , Haechan Mark Bong , Giovanni Beltrame

For tasks conducted in unknown environments with efficiency requirements, real-time navigation of multi-robot systems remains challenging due to unfamiliarity with surroundings.In this paper, we propose a novel multi-robot collaborative…

Robotics · Computer Science 2025-12-29 Qingquan Lin , Weining Lu , Litong Meng , Chenxi Li , Bin Liang

Multi-robot systems are an efficient method to explore and map an unknown environment. The simulataneous localization and mapping (SLAM) algorithm is common for single robot systems, however multiple robots can share respective map data in…

Robotics · Computer Science 2021-02-03 Henry Fielding Cappel

In this paper, we address the problem of autonomous multi-robot mapping, exploration and navigation in unknown, GPS-denied indoor or urban environments using a swarm of robots equipped with directional sensors with limited sensing…

Robotics · Computer Science 2021-03-08 Mohammad Saleh Teymouri , Subhrajit Bhattacharya

Accurate perception, state estimation and mapping are essential for safe robotic navigation as planners and controllers rely on these components for safety-critical decisions. However, existing mapping approaches often assume perfect pose…

We address multi-robot geometric task-and-motion planning (MR-GTAMP) problems in synchronous, monotone setups. The goal of the MR-GTAMP problem is to move objects with multiple robots to goal regions in the presence of other movable…

In indoor environments, multi-robot visual (RGB-D) mapping and exploration hold immense potential for application in domains such as domestic service and logistics, where deploying multiple robots in the same environment can significantly…

Robotics · Computer Science 2024-11-06 Sai Krishna Ghanta , Ramviyas Parasuraman

With the deepening of research on the SLAM system, the possibility of cooperative SLAM with multi-robots has been proposed. This paper presents a map matching and localization approach considering the cooperative SLAM of an aerial-ground…

Robotics · Computer Science 2020-12-07 Xuecheng Xu , Zexi Chen , Jiaxin Guo , Yue Wang , Yunkai Wang , Rong Xiong

In this article, a novel approach for merging 3D point cloud maps in the context of egocentric multi-robot exploration is presented. Unlike traditional methods, the proposed approach leverages state-of-the-art place recognition and learned…

In large unknown environments, search operations can be much more time-efficient with the use of multi-robot fleets by parallelizing efforts. This means robots must efficiently perform collaborative mapping (exploration) while…

Robotics · Computer Science 2023-03-07 Indraneel Patil , Rachel Zheng , Charvi Gupta , Jaekyung Song , Narendar Sriram , Katia Sycara