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| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.15215 |
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| _version_ | 1866917151458197504 |
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| author | Brorsson, Erik Ceder, Kristian Zhang, Ze Roselli, Sabino Francesco Erős, Endre Dahl, Martin Alenljung, Beatrice Lindblom, Jessica Bui, Thanh Dean, Emmanuel Svensson, Lennart Bengtsson, Kristofer Götvall, Per-Lage Åkesson, Knut |
| author_facet | Brorsson, Erik Ceder, Kristian Zhang, Ze Roselli, Sabino Francesco Erős, Endre Dahl, Martin Alenljung, Beatrice Lindblom, Jessica Bui, Thanh Dean, Emmanuel Svensson, Lennart Bengtsson, Kristofer Götvall, Per-Lage Åkesson, Knut |
| contents | The adoption of Autonomous Mobile Robots (AMRs) for internal logistics is accelerating, with most solutions emphasizing decentralized, onboard intelligence. While AMRs in indoor environments like factories can be supported by infrastructure, involving external sensors and computational resources, such systems remain underexplored in the literature. This paper presents a comprehensive overview of infrastructure-based AMR systems, outlining key opportunities and challenges. To support this, we introduce a reference architecture combining infrastructure-based sensing, on-premise cloud computing, and onboard autonomy. Based on the architecture, we review core technologies for localization, perception, and planning. We demonstrate the approach in a real-world deployment in a heavy-vehicle manufacturing environment and summarize findings from a user experience (UX) evaluation. Our aim is to provide a holistic foundation for future development of scalable, robust, and human-compatible AMR systems in complex industrial environments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_15215 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Infrastructure-based Autonomous Mobile Robots for Internal Logistics -- Challenges and Future Perspectives Brorsson, Erik Ceder, Kristian Zhang, Ze Roselli, Sabino Francesco Erős, Endre Dahl, Martin Alenljung, Beatrice Lindblom, Jessica Bui, Thanh Dean, Emmanuel Svensson, Lennart Bengtsson, Kristofer Götvall, Per-Lage Åkesson, Knut Robotics The adoption of Autonomous Mobile Robots (AMRs) for internal logistics is accelerating, with most solutions emphasizing decentralized, onboard intelligence. While AMRs in indoor environments like factories can be supported by infrastructure, involving external sensors and computational resources, such systems remain underexplored in the literature. This paper presents a comprehensive overview of infrastructure-based AMR systems, outlining key opportunities and challenges. To support this, we introduce a reference architecture combining infrastructure-based sensing, on-premise cloud computing, and onboard autonomy. Based on the architecture, we review core technologies for localization, perception, and planning. We demonstrate the approach in a real-world deployment in a heavy-vehicle manufacturing environment and summarize findings from a user experience (UX) evaluation. Our aim is to provide a holistic foundation for future development of scalable, robust, and human-compatible AMR systems in complex industrial environments. |
| title | Infrastructure-based Autonomous Mobile Robots for Internal Logistics -- Challenges and Future Perspectives |
| topic | Robotics |
| url | https://arxiv.org/abs/2512.15215 |