Multi-Agent Formation Navigation Using Diffusion-Based Trajectory Generation
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arXiv
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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866914258056380416 |
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| author | Quang, Hieu Do Truong-Quoc, Chien Van Tran, Quoc |
| author_facet | Quang, Hieu Do Truong-Quoc, Chien Van Tran, Quoc |
| contents | This paper introduces a diffusion-based planner for leader--follower formation control in cluttered environments. The diffusion policy is used to generate the trajectory of the midpoint of two leaders as a rigid bar in the plane, thereby defining their desired motion paths in a planar formation. While the followers track the leaders and form desired foramtion geometry using a distance-constrained formation controller based only on the relative positions in followers' local coordinates. The proposed approach produces smooth motions and low tracking errors, with most failures occurring in narrow obstacle-free space, or obstacle configurations that are not in the training data set. Simulation results demonstrate the potential of diffusion models for reliable multi-agent formation planning. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2601_10725 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Multi-Agent Formation Navigation Using Diffusion-Based Trajectory Generation Quang, Hieu Do Truong-Quoc, Chien Van Tran, Quoc Robotics Optimization and Control This paper introduces a diffusion-based planner for leader--follower formation control in cluttered environments. The diffusion policy is used to generate the trajectory of the midpoint of two leaders as a rigid bar in the plane, thereby defining their desired motion paths in a planar formation. While the followers track the leaders and form desired foramtion geometry using a distance-constrained formation controller based only on the relative positions in followers' local coordinates. The proposed approach produces smooth motions and low tracking errors, with most failures occurring in narrow obstacle-free space, or obstacle configurations that are not in the training data set. Simulation results demonstrate the potential of diffusion models for reliable multi-agent formation planning. |
| title | Multi-Agent Formation Navigation Using Diffusion-Based Trajectory Generation |
| topic | Robotics Optimization and Control |
| url | https://arxiv.org/abs/2601.10725 |