Learning Robot Policies from Sparse Success Signals via STL-Guided Stein Variational Policy Gradient

arXiv:2609.31606 · cs.RO · Submitted 2026-09-25 · Read on arXiv

cs.RO

Submitted: 2026-09-25

Updated: 2026-09-25

Terminology

• Robustness — 35× in this paper · explained in 5 episodes
• Signal Temporal Logic — 12× in this paper
• Reinforcement Learning — 9× in this paper · explained in 4 episodes
• Reward Shaping — 8× in this paper · explained in 2 episodes
• Benchmark — 7× in this paper · explained in 2 episodes
• Stein Variational Gradient Descent — 4× in this paper
• Ablation — 3× in this paper · explained in 1 episode
• Signal Temporal Logic (STL) — 3× in this paper · explained in 4 episodes
• Credit assignment — 2× in this paper · explained in 3 episodes
• Action Space — 1× in this paper · explained in 1 episode
• Actor — 1× in this paper · explained in 3 episodes
• Bayesian Inference — 1× in this paper · explained in 5 episodes
• Core — 1× in this paper · explained in 2 episodes
• Hybrid System — 1× in this paper · explained in 2 episodes
• PID Controller — 1× in this paper · explained in 2 episodes
• Proximal Policy Optimization (PPO) — 1× in this paper · explained in 5 episodes
• Q-learning — 1× in this paper · explained in 3 episodes
• Reward Function — 1× in this paper · explained in 2 episodes
• Sim-to-Real Transfer — 1× in this paper · explained in 2 episodes
• Task Decomposition — 1× in this paper · explained in 2 episodes

Sources

• STL-SVPIO: Signal Temporal Logic guided Stein Variational Path Integral Optimization
• Stein Variational Policy Gradient
• Reinforcement Learning for Flow-Matching Policies with Density Transport
• Proximal Policy Optimization Algorithms

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