| Multi-agent pathfinding with continuous time A Andreychuk, K Yakovlev, P Surynek, D Atzmon, R Stern Artificial Intelligence, 103662, 2022 | 224 | 2022 |
| Any-angle pathfinding for multiple agents based on SIPP algorithm K Yakovlev, A Andreychuk Proceedings of the International Conference on Automated Planning and …, 2017 | 75 | 2017 |
| Improving continuous-time conflict based search A Andreychuk, K Yakovlev, E Boyarski, R Stern Proceedings of the AAAI Conference on Artificial Intelligence 35 (13), 11220 …, 2021 | 46 | 2021 |
| Prioritized multi-agent path finding for differential drive robots K Yakovlev, A Andreychuk, V Vorobyev 2019 European Conference on Mobile Robots (ECMR), 1-6, 2019 | 32 | 2019 |
| Learn to follow: Decentralized lifelong multi-agent pathfinding via planning and learning A Skrynnik, A Andreychuk, M Nesterova, K Yakovlev, A Panov Proceedings of the AAAI Conference on Artificial Intelligence 38 (16), 17541 …, 2024 | 23* | 2024 |
| Transpath: Learning heuristics for grid-based pathfinding via transformers D Kirilenko, A Andreychuk, A Panov, K Yakovlev Proceedings of the AAAI Conference on Artificial Intelligence 37 (10), 12436 …, 2023 | 21 | 2023 |
| Two techniques that enhance the performance of multi-robot prioritized path planning A Andreychuk, K Yakovlev arXiv preprint arXiv:1805.01270, 2018 | 21 | 2018 |
| Revisiting bounded-suboptimal safe interval path planning K Yakovlev, A Andreychuk, R Stern Proceedings of the International Conference on Automated Planning and …, 2020 | 20 | 2020 |
| Combining safe interval path planning and constrained path following control: preliminary results K Yakovlev, A Andreychuk, J Belinskaya, D Makarov Interactive Collaborative Robotics: 4th International Conference, ICR 2019 …, 2019 | 18 | 2019 |
| Decentralized monte carlo tree search for partially observable multi-agent pathfinding A Skrynnik, A Andreychuk, K Yakovlev, A Panov Proceedings of the AAAI Conference on Artificial Intelligence 38 (16), 17531 …, 2024 | 13 | 2024 |
| When to switch: planning and learning for partially observable multi-agent pathfinding A Skrynnik, A Andreychuk, K Yakovlev, AI Panov IEEE Transactions on Neural Networks and Learning Systems, 2023 | 13 | 2023 |
| Applying MAPP algorithm for cooperative path finding in urban environments A Andreychuk, K Yakovlev Interactive Collaborative Robotics: Second International Conference, ICR …, 2017 | 11 | 2017 |
| Метод автоматического планирования совокупности траекторий для навигации беспилотных транспортных средств КС Яковлев, ЕС Баскин, АА Андрейчук Управление большими системами: сборник трудов, 306-342, 2015 | 10 | 2015 |
| Planning and learning in multi-agent path finding KS Yakovlev, AA Andreychuk, AA Skrynnik, AI Panov Doklady Mathematics 106 (Suppl 1), S79-S84, 2022 | 9 | 2022 |
| Pathfinding in stochastic environments: learning vs planning A Skrynnik, A Andreychuk, K Yakovlev, A Panov PeerJ Computer Science 8, e1056, 2022 | 9 | 2022 |
| POGEMA: partially observable grid environment for multiple agents A Skrynnik, A Andreychuk, K Yakovlev, AI Panov arXiv preprint arXiv:2206.10944, 2022 | 9 | 2022 |
| Towards time-optimal any-angle path planning with dynamic obstacles K Yakovlev, A Andreychuk Proceedings of the International Conference on Automated Planning and …, 2021 | 9 | 2021 |
| Multi-agent path finding with kinematic constraints via conflict based search A Andreychuk Artificial Intelligence: 18th Russian Conference, RCAI 2020, Moscow, Russia …, 2020 | 9 | 2020 |
| МЕТОДЫ ПЛАНИРОВАНИЯ ТРАЕКТОРИИ НА ПЛОСКОСТИ С УЧЕТОМ ГЕОМЕТРИЧЕСКИХ ОГРАНИЧЕНИЙ1 АА Андрейчук, КС Яковлев Известия Российской академии наук. Теория и системы управления, 125-140, 2017 | 8 | 2017 |
| Safe interval path planning and flatness-based control for navigation of a mobile robot among static and dynamic obstacles KS Yakovlev, AA Andreychuk, JS Belinskaya, DA Makarov Automation and Remote Control 83 (6), 903-918, 2022 | 7 | 2022 |
Константин Сергеевич Яковлев (Kon...ФИЦ ИУ РАН, ВШЭ, МФТИ, AIRIZweryfikowany adres z isa.ru
