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Decentralized Unlabeled Multi-agent Navigation in Continuous Space
P. 186–200.
Keywords: групповая робототехникаинтеллектуальная робототехникаautonomous navigationautonomous navigation of a mobile robotавтономная навигация мобильного робота;collective roboticsмногоагентное планированиеcollaborative roboticsmulti-agent path findingIntellectual RoboticsMulti-agent robotic systemMulti-agent path planningНавигация мобильных роботовMobile robots navigation
Irina Petrovna Karpova, Pattern Recognition and Image Analysis 2025 Vol. 35 No. 4 P. 1138–1144
A solution to the problem of redistributing agents between groups based on simulating a form of social parasitism in ants known as slave-making is considered. To provide a comprehensive solution, the problem is integrated with a method of orientation based on visual landmarks and a compass, including route memorization and return. The models and mechanisms ...
Added: April 29, 2026
Springer, 2026.
The two volume set LNAI 16303 + 16304 constitutes the refereed proceedings of the 10th International Conference on Interactive Collaborative Robotics, ICR 2025, held in Hanoi, Vietnam, during November 10–13, 2025. The 58 full papers presented in these two volumes were carefully reviewed and selected from 143 submissions. The papers are organized in the following topical sections:
Part ...
Added: March 17, 2026
Dergachev S., Yakovlev K., , in: 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).: IEEE, 2025. P. 12456–12463.
Decentralized multi-agent navigation under uncertainty is a complex task that arises in numerous robotic applications. It requires collision avoidance strategies that account for both kinematic constraints, sensing and action execution noise. In this paper, we propose a novel approach that integrates the Model Predictive Path Integral (MPPI) with a probabilistic adaptation of Optimal Reciprocal Collision ...
Added: March 2, 2026
Karpova I. P., Robotics and Autonomous Systems 2025 Vol. 193 Article 105082
This paper describes a method for mobile robot navigation that is similar to the navigation mechanism of social insects. Unlike other bio-inspired methods that mimic certain morphological features of animals or separate natural mechanisms, the proposed approach is based on the phenomenology of the behaviour of some ant species during collective foraging. This method does ...
Added: June 3, 2025
Dergachev S., Yakovlev K., , in: 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE).: IEEE, 2024. Ch. n/a P. 1489–1494.
Avoiding collisions is the core problem in multiagent navigation. In decentralized settings, when agents have limited communication and sensory capabilities, collisions are typically avoided in a reactive fashion, relying on local ob-servations/communications. Prominent collision avoidance techniques, e.g. ORCA, are computationally efficient and scale well to a large number of agents. However, in numerous scenarios, involving ...
Added: May 5, 2025
Kirill Muravyev, Melekhin A., Yudin D. et al., IEEE Robotics and Automation Letters 2025 Vol. 10 No. 4 P. 3126–3133
Mapping is one of the crucial tasks enabling autonomous navigation of a mobile robot. Conventional mapping methods output a dense geometric map representation, e.g. an occupancy grid, which is not trivial to keep consistent for prolonged runs covering large environments. Meanwhile, capturing the topological structure of the workspace enables fast path planning, is typically less ...
Added: March 3, 2025
I.P. Karpova, V. E. Karpov, Automation and Remote Control 2024 Vol. 85 No. 7 P. 641–651
This paper explores the problem of influencing the environment by a group of autonomous robots through the creation and use of road infrastructure. The model object is ant roads (trails). We identify the main aspects of the behavior of different ant species in the process of collective foraging, and actions that together lead to the ...
Added: November 6, 2024
Dergachev S., Yakovlev K., В кн.: Сборник трудов XIV Всероссийского совещания по проблемам управления ВСПУ-2024.: Институт проблем управления им. В.А. Трапезникова РАН, 2024. С. 1630–1634.
Added: September 26, 2024
Dergachev S., Yakovlev K., , in: ECAI 2024. 27th European Conference on Artificial Intelligence, October 19 – 24 October 2024, Santiago de Compostela, Spain – Including 13th Conference on Prestigious Applications of Intelligent Systems (PAIS 2024).: IOS Press, 2024. P. 4344–4351.
Added: September 11, 2024