MR.CAP: Multi-Robot Joint Control and Planning for Object Transport
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866916101017829376 |
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| author | Jaafar, Hussein Ali Kao, Cheng-Hao Saeedi, Sajad |
| author_facet | Jaafar, Hussein Ali Kao, Cheng-Hao Saeedi, Sajad |
| contents | With the recent influx in demand for multi-robot systems throughout industry and academia, there is an increasing need for faster, robust, and generalizable path planning algorithms. Similarly, given the inherent connection between control algorithms and multi-robot path planners, there is in turn an increased demand for fast, efficient, and robust controllers. We propose a scalable joint path planning and control algorithm for multi-robot systems with constrained behaviours based on factor graph optimization. We demonstrate our algorithm on a series of hardware and simulated experiments. Our algorithm is consistently able to recover from disturbances and avoid obstacles while outperforming state-of-the-art methods in optimization time, path deviation, and inter-robot errors. See the code and supplementary video for experiments. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2401_11634 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | MR.CAP: Multi-Robot Joint Control and Planning for Object Transport Jaafar, Hussein Ali Kao, Cheng-Hao Saeedi, Sajad Robotics With the recent influx in demand for multi-robot systems throughout industry and academia, there is an increasing need for faster, robust, and generalizable path planning algorithms. Similarly, given the inherent connection between control algorithms and multi-robot path planners, there is in turn an increased demand for fast, efficient, and robust controllers. We propose a scalable joint path planning and control algorithm for multi-robot systems with constrained behaviours based on factor graph optimization. We demonstrate our algorithm on a series of hardware and simulated experiments. Our algorithm is consistently able to recover from disturbances and avoid obstacles while outperforming state-of-the-art methods in optimization time, path deviation, and inter-robot errors. See the code and supplementary video for experiments. |
| title | MR.CAP: Multi-Robot Joint Control and Planning for Object Transport |
| topic | Robotics |
| url | https://arxiv.org/abs/2401.11634 |