A Multi-Robot Collaborative Exploration Method Based on Deep Reinforcement Learning and Knowledge Distillation
Multi-robot collaborative autonomous exploration in communication-constrained scenarios is essential in areas such as search and rescue. During the exploration process, the robot teams must minimize the occurrence of redundant scanning of the environment. To this end, we propose to view the robot te...
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| Format: | Article |
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MDPI AG
2025-01-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/13/1/173 |
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| author | Rui Wang Ming Lyu Jie Zhang |
| author_facet | Rui Wang Ming Lyu Jie Zhang |
| author_sort | Rui Wang |
| collection | DOAJ |
| description | Multi-robot collaborative autonomous exploration in communication-constrained scenarios is essential in areas such as search and rescue. During the exploration process, the robot teams must minimize the occurrence of redundant scanning of the environment. To this end, we propose to view the robot team as an agent and obtain a policy network that can be centrally executed by training with an improved SAC deep reinforcement learning algorithm. In addition, we transform the obtained policy network into distributed networks that can be adapted to communication-constrained scenarios using knowledge distillation. Our proposed method offers an innovative solution to the decision-making problem for multiple robots. We conducted experiments on our proposed method within simulated environments. The experimental results show the adaptability of our proposed method to various sizes of environments and its superior performance compared to the current mainstream methods. |
| format | Article |
| id | doaj-art-dffa1b1f795d4a6eb8ab5ad5ab6cf76f |
| institution | Kabale University |
| issn | 2227-7390 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj-art-dffa1b1f795d4a6eb8ab5ad5ab6cf76f2025-01-10T13:18:30ZengMDPI AGMathematics2227-73902025-01-0113117310.3390/math13010173A Multi-Robot Collaborative Exploration Method Based on Deep Reinforcement Learning and Knowledge DistillationRui Wang0Ming Lyu1Jie Zhang2School of Automation, Nanjing University of Science and Technology, Nanjing 210094, ChinaSchool of Automation, Nanjing University of Science and Technology, Nanjing 210094, ChinaSchool of Automation, Nanjing University of Science and Technology, Nanjing 210094, ChinaMulti-robot collaborative autonomous exploration in communication-constrained scenarios is essential in areas such as search and rescue. During the exploration process, the robot teams must minimize the occurrence of redundant scanning of the environment. To this end, we propose to view the robot team as an agent and obtain a policy network that can be centrally executed by training with an improved SAC deep reinforcement learning algorithm. In addition, we transform the obtained policy network into distributed networks that can be adapted to communication-constrained scenarios using knowledge distillation. Our proposed method offers an innovative solution to the decision-making problem for multiple robots. We conducted experiments on our proposed method within simulated environments. The experimental results show the adaptability of our proposed method to various sizes of environments and its superior performance compared to the current mainstream methods.https://www.mdpi.com/2227-7390/13/1/173multi-robotautonomous explorationdeep reinforcement learning |
| spellingShingle | Rui Wang Ming Lyu Jie Zhang A Multi-Robot Collaborative Exploration Method Based on Deep Reinforcement Learning and Knowledge Distillation Mathematics multi-robot autonomous exploration deep reinforcement learning |
| title | A Multi-Robot Collaborative Exploration Method Based on Deep Reinforcement Learning and Knowledge Distillation |
| title_full | A Multi-Robot Collaborative Exploration Method Based on Deep Reinforcement Learning and Knowledge Distillation |
| title_fullStr | A Multi-Robot Collaborative Exploration Method Based on Deep Reinforcement Learning and Knowledge Distillation |
| title_full_unstemmed | A Multi-Robot Collaborative Exploration Method Based on Deep Reinforcement Learning and Knowledge Distillation |
| title_short | A Multi-Robot Collaborative Exploration Method Based on Deep Reinforcement Learning and Knowledge Distillation |
| title_sort | multi robot collaborative exploration method based on deep reinforcement learning and knowledge distillation |
| topic | multi-robot autonomous exploration deep reinforcement learning |
| url | https://www.mdpi.com/2227-7390/13/1/173 |
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