Enhancing Indoor Mobility with Connected Sensor Nodes: A Real-Time, Delay-Aware Cooperative Perception Approach

• URL: http://arxiv.org/abs/2411.02624v1
• Date: Mon, 04 Nov 2024 21:31:45 GMT
• Title: Enhancing Indoor Mobility with Connected Sensor Nodes: A Real-Time, Delay-Aware Cooperative Perception Approach
• Authors: Minghao Ning, Yaodong Cui, Yufeng Yang, Shucheng Huang, Zhenan Liu, Ahmad Reza Alghooneh, Ehsan Hashemi, Amir Khajepour,
• Abstract summary: This paper presents a novel real-time, delay-aware cooperative perception system for indoor environments. The system features delay-aware global perception to synchronize and aggregate data across nodes. Our experiments, compared to baselines, demonstrate significant improvements in detection accuracy and robustness against delays.
• Score: 11.427488895308073
• License:
• Abstract: This paper presents a novel real-time, delay-aware cooperative perception system designed for intelligent mobility platforms operating in dynamic indoor environments. The system contains a network of multi-modal sensor nodes and a central node that collectively provide perception services to mobility platforms. The proposed Hierarchical Clustering Considering the Scanning Pattern and Ground Contacting Feature based Lidar Camera Fusion improve intra-node perception for crowded environment. The system also features delay-aware global perception to synchronize and aggregate data across nodes. To validate our approach, we introduced the Indoor Pedestrian Tracking dataset, compiled from data captured by two indoor sensor nodes. Our experiments, compared to baselines, demonstrate significant improvements in detection accuracy and robustness against delays. The dataset is available in the repository: https://github.com/NingMingHao/MVSLab-IndoorCooperativePerception

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