3 papers
cs.RO2026
TACO: Temporal Consensus Optimization for Continual Neural Mapping
Xunlan Zhou, Hongrui Zhao, Negar Mehr
Neural implicit mapping has emerged as a powerful paradigm for robotic navigation and scene understanding. However, real-world robotic deployment requires continual adaptation to c…
cs.RO2026
UDON: Uncertainty-weighted Distributed Optimization for Multi-Robot Neural Implicit Mapping under Extreme Communication Constraints
Hongrui Zhao, Xunlan Zhou, Boris Ivanovic +1
Multi-robot mapping with neural implicit representations enables the compact reconstruction of complex environments. However, it demands robustness against communication challenges…
cs.RO2025
RAMEN: Real-time Asynchronous Multi-agent Neural Implicit Mapping
Hongrui Zhao, Boris Ivanovic, Negar Mehr
Multi-agent neural implicit mapping allows robots to collaboratively capture and reconstruct complex environments with high fidelity. However, existing approaches often rely on syn…