Cooperative Localization and Mapping

Stipes, J.A.; Hawthorne, Ryan; Scheidt, David; Pacifico, Daniele

doi:10.1109/icnsc.2006.1673213

Cited by 18 publications

(8 citation statements)

References 12 publications

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“…There are solutions that implemented cooperative indoor mapping by using only UGVs [15][16][17][18][19]. In [15], heterogeneous robots were used in 2D and 3D area mapping using laser scanners, performing 3D and 2D cooperative mapping via autonomous agent navigation.…”

Section: Multiple Robots In Environment Mappingmentioning

confidence: 99%

“…Here, each robot builds a local map and sends the relevant data to a central server, where the data are joined with existing data using join-compatibility branch and bound (JCBB) implementation. In [16], the authors adapted the FastSLAM algorithm for multiple agents by also using laser scanners. Presenting a version of FastSLAM adapted to multiple UGV robots, it could perform cooperative mapping with the stigmergic potential field (SPF) technique, which represents behavioral influences of gathered data from the operational environment of one of the agents.…”

Section: Multiple Robots In Environment Mappingmentioning

confidence: 99%

See 1 more Smart Citation

Honeycomb Map: A Bioinspired Topological Map for Indoor Search and Rescue Unmanned Aerial Vehicles

Rosa

Wehrmeister

Brito

et al. 2020

Sensors

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The use of robots to map disaster-stricken environments can prevent rescuers from being harmed when exploring an unknown space. In addition, mapping a multi-robot environment can help these teams plan their actions with prior knowledge. The present work proposes the use of multiple unmanned aerial vehicles (UAVs) in the construction of a topological map inspired by the way that bees build their hives. A UAV can map a honeycomb only if it is adjacent to a known one. Different metrics to choose the honeycomb to be explored were applied. At the same time, as UAVs scan honeycomb adjacencies, RGB-D and thermal sensors capture other data types, and then generate a 3D view of the space and images of spaces where there may be fire spots, respectively. Simulations in different environments showed that the choice of metric and variation in the number of UAVs influence the number of performed displacements in the environment, consequently affecting exploration time and energy use.

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Section: Multiple Robots In Environment Mappingmentioning

confidence: 99%

Section: Multiple Robots In Environment Mappingmentioning

confidence: 99%

Honeycomb Map: A Bioinspired Topological Map for Indoor Search and Rescue Unmanned Aerial Vehicles

Rosa

Wehrmeister

Brito

et al. 2020

Sensors

View full text Add to dashboard Cite

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“…While this technique effectively decentralizes control, exchange of map information is not enough to prevent inefficient cooperative behaviors. This approach also required known starting positions and failed to provide a robust mechanism for map merging [8].…”

Section: Introductionmentioning

confidence: 99%

“…Several researchers have suggested stigmergy methods [7] and [8]. Stigmergy is a mechanism of spontaneous, indirect coordination between agents or actions, where a trace left in the environment by an action stimulates the performance of subsequent actions, by the same or by different agents.…”

Section: Introductionmentioning

confidence: 99%

Multi-robot exploration and fire searching

Marjovi

Nunes

Marques

et al. 2009

2009 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-Exploration of an unknown environment is a fundamental concern in mobile robotics. This paper presents an approach for cooperative multi-robot exploration, fire searching and mapping in an unknown environment. The proposed approach aims to minimize the overall exploration time, making it possible to localize fire sources in an efficient way. In order to achieve this goal, the robots should cooperate in an effective way, so they can individually and simultaneously explore different areas of the environment while they identify fire sources. The proposed approach employs a decentralized frontier based exploration method which evaluates the cost-gain ratio to navigate to target way-points. The target way-points are obtained by an A* search variant algorithm. The potential field method is used to control the robots motion while avoiding obstacles. When a robot detects a fire, it estimates the flame's position by triangulation. The communication between the robots is done in a decentralized control way where they share the necessary data to generate the map of the environment and to perform cooperative actions in a behavioral decision making way. This paper presents simulation and experimental results of the proposed exploration and fire search method and concludes with a discussion of the obtained results and future improvements.

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“…Methods based on stimergy fields for cooperation have been recently employed in the context of robotic exploration [13], [14], [15]. They rely on a mechanism of indirect communication among the agents which allows their actions to be influenced by a trace left previously in the environment by the robot.…”

Section: Introductionmentioning

confidence: 99%

Integration of virtual pheromones for mapping/exploration of environments by using multiple robots

Oliveira

Calvo

Romero

2014

5th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics

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Abstract-The multiple robot coordination strategies have several advantages when compared to strategies based on a single robot, in terms of flexibility, gain of information and reduction of map building time. In this paper, a local pheromone map integration method is proposed based on the inter-robot observations, considering a method for the environment exploration named the Inverse Ant System-Based Surveillance System strategy (IAS-SS). Simulation results show that the map integration method is efficient, the trials are performed considering a variable number of robots in an indoor environment. Results obtained from several experiments confirm that the integration process is effective and suitable to execute the control of the access to pheromones in a virtual way.

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Cooperative Localization and Mapping

Cited by 18 publications

References 12 publications

Honeycomb Map: A Bioinspired Topological Map for Indoor Search and Rescue Unmanned Aerial Vehicles

Honeycomb Map: A Bioinspired Topological Map for Indoor Search and Rescue Unmanned Aerial Vehicles

Multi-robot exploration and fire searching

Integration of virtual pheromones for mapping/exploration of environments by using multiple robots

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