DUGM-R: Uncertainty-Aware Dynamic Grid Mapping and Risk-Triggered Recovery for Learned Local Navigation

arXiv:2609.27338 · cs.RO · Submitted 2026-09-23 · Read on arXiv

cs.RO

Submitted: 2026-09-23

Updated: 2026-09-23

Terminology

Reinforcement Learning — 9× in this paper · explained in 4 episodes
Ablation — 6× in this paper · explained in 1 episode
Benchmark — 6× in this paper · explained in 2 episodes
Deep Reinforcement Learning — 6× in this paper · explained in 2 episodes
Adaptation — 3× in this paper · explained in 1 episode
Clustering — 2× in this paper · explained in 2 episodes
Dynamic Window Approach — 2× in this paper
Fine-Tuning — 2× in this paper · explained in 5 episodes
IEEE International Conference on Robotics and Automation — 2× in this paper
Regularization — 2× in this paper · explained in 3 episodes
Reward Shaping — 2× in this paper · explained in 2 episodes
Abstraction — 1× in this paper · explained in 1 episode
Attention Mechanism — 1× in this paper · explained in 3 episodes
Calibration — 1× in this paper · explained in 7 episodes
Deep Reinforcement Learning (DRL) — 1× in this paper · explained in 2 episodes
Dynamic Uncertainty Grid Map — 1× in this paper
Generalization — 1× in this paper · explained in 13 episodes
Imitation Learning (IL) — 1× in this paper · explained in 2 episodes
Optimal Reciprocal Collision Avoidance — 1× in this paper
Proximal Policy Optimization (PPO) — 1× in this paper · explained in 5 episodes
Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
Risk Value Function — 1× in this paper
Two-stage training — 1× in this paper · explained in 2 episodes

Sources

End-to-End Safe Reinforcement Learning through Barrier Functions for Safety-Critical Continuous Control Tasks

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