Real-World Deployment of Cloud-based Autonomous Mobility Systems for Outdoor and Indoor Environments
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866911520572571648 |
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| author | Yang, Yufeng Ning, Minghao Shu, Keqi Saleh, Aladdin Hashemi, Ehsan Khajepour, Amir |
| author_facet | Yang, Yufeng Ning, Minghao Shu, Keqi Saleh, Aladdin Hashemi, Ehsan Khajepour, Amir |
| contents | Autonomous mobility systems increasingly operate in dense and dynamic environments where perception occlusions, limited sensing coverage, and multi-agent interactions pose major challenges. While onboard sensors provide essential local perception, they often struggle to maintain reliable situational awareness in crowded urban or indoor settings. This article presents the Cloud-based Autonomous Mobility (CAM) framework, a generalized architecture that integrates infrastructure-based intelligent sensing with cloud-level coordination to enhance autonomous operations. The system deploys distributed Intelligent Sensor Nodes (ISNs) equipped with cameras, LiDAR, and edge computing to perform multi-modal perception and transmit structured information to a cloud platform via high-speed wireless communication. The cloud aggregates observations from multiple nodes to generate a global scene representation for other autonomous modules, such as decision making, motion planning, etc. Real-world deployments in an urban roundabout and a hospital-like indoor environment demonstrate improved perception robustness, safety, and coordination for future intelligent mobility systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_21676 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Real-World Deployment of Cloud-based Autonomous Mobility Systems for Outdoor and Indoor Environments Yang, Yufeng Ning, Minghao Shu, Keqi Saleh, Aladdin Hashemi, Ehsan Khajepour, Amir Robotics Networking and Internet Architecture Autonomous mobility systems increasingly operate in dense and dynamic environments where perception occlusions, limited sensing coverage, and multi-agent interactions pose major challenges. While onboard sensors provide essential local perception, they often struggle to maintain reliable situational awareness in crowded urban or indoor settings. This article presents the Cloud-based Autonomous Mobility (CAM) framework, a generalized architecture that integrates infrastructure-based intelligent sensing with cloud-level coordination to enhance autonomous operations. The system deploys distributed Intelligent Sensor Nodes (ISNs) equipped with cameras, LiDAR, and edge computing to perform multi-modal perception and transmit structured information to a cloud platform via high-speed wireless communication. The cloud aggregates observations from multiple nodes to generate a global scene representation for other autonomous modules, such as decision making, motion planning, etc. Real-world deployments in an urban roundabout and a hospital-like indoor environment demonstrate improved perception robustness, safety, and coordination for future intelligent mobility systems. |
| title | Real-World Deployment of Cloud-based Autonomous Mobility Systems for Outdoor and Indoor Environments |
| topic | Robotics Networking and Internet Architecture |
| url | https://arxiv.org/abs/2505.21676 |