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CoopUQ: Robust Multi-Robot Social Navigation via Uncertainty-Aware Cooperative Forecasting

Paper recorded by Signals 4 on 2026-10-19 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-19 on arXiv · recorded by Signals 4 on 2026-10-20

Category: cs.AI · 人工智能 · first seen 2026-10-20

Abstract

Reinforcement learning enables mobile robots to make fast and scalable navigation decisions in constrained human-shared environments. However, directly extending single-robot approaches to multi-robot settings often fails to ensure safety and efficiency, especially under occlusions and out-of-distribution (OOD) scenarios, where individual robots may overlook potential risks or make inaccurate pred

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#243 most recent of 960 cs.AI papers we have recorded · ↑ newer: Reinforcement Learning with Visually Attributable On-Policy Self-Disti · ↓ older: Where is Physical RSI capability from? An Observational Scaling Law of
Cite this page: CoopUQ: Robust Multi-Robot Social Navigation via Uncertainty-Aware Cooperative Forecasting: the #243 most recent of 960 cs.AI papers we have recorded (as of 2026-10-19). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/coopuq-robust-multi-robot-social-navigation-via-uncertainty-aware-cooperative-fo.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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