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Asynchronous Collaborative Localization by Integrating Spatiotemporal Graph Learning with Model-Based Estimation
In this paper, we introduce a novel approach that integrates uncertainty-aware spatiotemporal graph learning and model-based state estimation for a team of robots to collaboratively localize objects.
Simultaneous Learning from Human Pose and Object Cues for Real-Time Activity Recognition
Real-time human activity recognition plays an essential role in real-world human-centered robotics applications, such as assisted living and human-robot collaboration.
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