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Found 6 papers, 0 papers with code
A Belief Propagation Approach for Direct Multipath-Based SLAM
This factor graph is the starting point for the development of an efficient belief propagation (BP) method for multipath-based SLAM that directly uses received radio signals as measurements.
A BP Method for Track-Before-Detect
Our proposed method is based on a new statistical model that introduces a new object hypothesis for each data cell of the raw sensor measurements.
Neural Enhanced Belief Propagation for Multiobject Tracking
State-of-the-art MOT methods fully rely on a statistical model and typically use preprocessed sensor data as measurements.
Data Fusion for Radio Frequency SLAM with Robust Sampling
A promising approach to address this problem is to exchange radio signals between mobile agents and static physical anchors (PAs) that bounce off flat surfaces in the indoor environment.
Neural Enhanced Belief Propagation for Data Association in Multiobject Tracking
Situation-aware technologies enabled by multiobject tracking (MOT) methods will create new services and applications in fields such as autonomous navigation and applied ocean sciences.
Neural Enhanced Belief Propagation for Cooperative Localization
Location-aware networks will introduce innovative services and applications for modern convenience, applied ocean sciences, and public safety.
