ACHORD: Communication-Aware Multi-Robot Coordination With Intermittent Connectivity

Silva, Maíra Saboia da; Clark, Lillian; Thangavelu, Vivek; Edlund, Jeffrey A.; Otsu, Kyohei; Correa, Gustavo J.; Varadharajan, Vivek Shankar; Santamaria-Navarro, Àngel; Touma, Thomas; Bouman, Amanda; Melikyan, Hovhannes; Pailevanian, Torkom; Kim, Sung-Kyun; Archanian, Avak; Vaquero, Tiago Stegun; Beltrame, Giovanni; Napp, Nils; Pessin, Gustavo; Agha–mohammadi, Ali–akbar

doi:10.1109/lra.2022.3193240

Cited by 12 publications

(4 citation statements)

References 35 publications

(38 reference statements)

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“…The autonomous coordination of the robots is addressed by describing the whole task allocation problem using Planning Domain Definition Language (PDDL) (Fox and Long, 2002) solved by the OPTIC solver (Benton et al, 2012). During the final circuit of the DARPA SubT, the team tested an exploration approach that takes into account connectivity between robots (Saboia et al, 2022).…”

Section: Overview Of the Darpa Subt Challenge Teamsmentioning

confidence: 99%

Autonomous Multi-robot Exploration with Ground Vehicles in DARPA Subterranean Challenge Finals

Bayer¹,

Čížek²,

Faigl³

2023

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Autonomous navigation and multi-robot exploration framework for ground robots are key parts of the robotic system deployed by the team CTU-CRAS-NORLAB in the final event of the Subterranean (SubT) Challenge organized by the Defense Advanced Research Projects Agency (DARPA) in 2021. The SubT Challenge aimed to advance technologies related to search-and-rescue missions with multi-robot systems in underground environments where communication is unavailable and global navigation satellite systems are denied. This field report describes the developed multi- robot exploration framework focusing on planning, exploration, and traversability estimation for a heterogeneous team of ground vehicles in large-scale rough terrains and multi-robot coordination with limited communication. The developed method employs a dense local mapping for precise traversability estimation combined with a sparse topometrical map shareable between multiple robots and is thus used in the decision-making of the exploration strategy. The topometrical map is designed to support the decentralized coordination of heterogeneous teams of robots, which is demonstrated by deploying the developed framework in the SubT competitions. The framework has been employed in the Virtual track for the full autonomous control of the ground robots, where our team scored second. Besides, in the Systems track, a human supervisor exploited autonomous behaviors provided by the proposed framework to control a heterogeneous team of six ground robots. We report on real-world experimental results from the deployment of the SubT Challenge. Furthermore, we present results from the post-event testing of the SubT Challenge, where three quadruped robots controlled by the framework explored over five hundred meters fully autonomously.

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Section: Overview Of the Darpa Subt Challenge Teamsmentioning

confidence: 99%

Autonomous Multi-robot Exploration with Ground Vehicles in DARPA Subterranean Challenge Finals

Bayer¹,

Čížek²,

Faigl³

2023

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“…Saboia et al [ 10 ] proposed another communication-aware algorithm that adapts to changes in the dynamic network by using radio propagation models to predict link quality. A connectivity map of the signal quality over the explored area is maintained throughout the expedition.…”

Section: Related Workmentioning

confidence: 99%

CARA: Connectivity-Aware Relay Algorithm for Multi-Robot Expeditions

Abu-Aisheh

Bronzino

Salaün

et al. 2022

Sensors

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The exploration of unknown environments is an essential application of multi-robot systems, particularly in critical missions, such as hazard detection and search and rescue. These missions share the need to reach full coverage of the explorable space in the shortest time possible. To minimize the completion time, robots in the fleet must be able to reliably exchange information about the environment with one another. One of the main methods to expand coverage is by placing relays. Existing relay-placement algorithms tend to either require prior knowledge of the environment, or they rely on maintaining specific distances between the relays and the rest of the robots. These approaches lack flexibility and adaptability to the environment. This paper introduces the “Connectivity-Aware Relay Algorithm” (CARA), a dynamic context-aware relay-placement algorithm that does not require any prior knowledge of the environment. We compare CARA against a state-of-the-art distance-based relay-placement algorithm. Our results demonstrate that CARA outperformed the state-of-the-art algorithm in terms of the time to completion by a factor of 10 as it placed, on average, half the number of relays.

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“…Multi-robot exploration of an unknown space is a fundamental task for mobile robot systems. A wide range of applications for mobile robot exploration using a group of robots can be mentioned, including autonomous transportation [ 1 ], industry [ 2 , 3 ], healthcare [ 4 ], rescue [ 5 , 6 , 7 ], and agriculture [ 8 , 9 , 10 , 11 ]. A robot must be able to navigate in a known or unknown environment [ 12 ] without human assistance.…”

Section: Introductionmentioning

confidence: 99%

Multi-Robot Exploration of Unknown Space Using Combined Meta-Heuristic Salp Swarm Algorithm and Deterministic Coordinated Multi-Robot Exploration

Romeh

Mirjalili

2023

Sensors

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Multi-robot exploration means constructing a finite map using a group of robots in an obstacle chaotic space. Uncertainties are reduced by distributing search tasks to robots and computing the best action in real time. Many previous methods are based on deterministic or meta-heuristic algorithms, but limited work has combined both techniques to consolidate both classes’ benefits and alleviate their drawbacks. This paper proposes a new hybrid method based on deterministic coordinated multi-robot exploration (CME) and the meta-heuristic salp swarm algorithm (SSA) to perform the search of a space. The precedence of adjacent cells around a robot is determined by deterministic CME using cost and utility. Then, the optimization process of the search space, improving the overall solution, is achieved utilizing the SSA. Three performance measures are considered to evaluate the performance of the proposed method: run time, percentage of the explored area, and the number of times when a method failed to continue a complete run. Experimental results compared four different methods, CME-GWO, CME-GWOSSA, CME-SCA, and CME, over seven maps with extra complexity varying from simple to complex. The results demonstrate how the proposed CME-SSA can outperform the four other methods. Moreover, the simulation results demonstrate that the proposed CME-SSA effectively distributes the robots over the search space to run successfully and obtain the highest exploration rate in less time.

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ACHORD: Communication-Aware Multi-Robot Coordination With Intermittent Connectivity

Cited by 12 publications

References 35 publications

Autonomous Multi-robot Exploration with Ground Vehicles in DARPA Subterranean Challenge Finals

Autonomous Multi-robot Exploration with Ground Vehicles in DARPA Subterranean Challenge Finals

CARA: Connectivity-Aware Relay Algorithm for Multi-Robot Expeditions

Multi-Robot Exploration of Unknown Space Using Combined Meta-Heuristic Salp Swarm Algorithm and Deterministic Coordinated Multi-Robot Exploration

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