arXiv Machine Learning By Takieddine Soualhi (CHROMA), Jacques Saraydaryan (CPE, CHROMA), Laetitia Matignon (UCBL)

Towards Socially Compliant Navigation in Deep Reinforcement Learning via Proxemics-Based Reward Modeling

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arXiv:2608. 12917v1 Announce Type: new Abstract: Developing effective robot navigation methods in crowded environments is essential for real-world applications.

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arXiv AI
Jul 14

Think When It Matters: Conditional VLM Reasoning for Social Navigation with RL Policies

arXiv:2607. 10991v1 Announce Type: cross Abstract: As mobile robots become more integrated into everyday human environments, social robot navigation is becoming essential for ensuring human comfort, safety, and trust.

By Ali Ahmadi, Hamed Rahimi, Adrien Jacquet Cretides, Marie Samson, Mahdi Khoramshahi, Mohamed Chetouani
arXiv Machine Learning
Aug 28

Diffusion Policies for Short-Horizon Planning in Robot Crowd Navigation

The paper introduces Planning Diffusion Policy Optimization (PDPO), an offline‑to‑online reinforcement‑learning framework that employs a diffusion policy to produce short‑horizon action chunks for robot crowd navigation. PDPO is pretrained on collision‑avoidance demonstrations and fine‑tuned online with PPO, generating five‑step action sequences applied in a receding‑horizon manner. The authors also identify a benchmark artifact where agents can leave the valid domain without explicit boundary constraints, and they mitigate this by treating boundary violations as collisions, leading to improved success rates over strong baselines.

By Wendong Li, Jochen Garcke
arXiv AI
Jun 9

HA-VLN 2.0: An Open Benchmark and Leaderboard for Human-Aware Navigation in Discrete and Continuous Environments with Dynamic Multi-Human Interactions

arXiv:2503. 14229v4 Announce Type: replace Abstract: Vision-and-Language Navigation (VLN) has been studied mainly in either discrete or continuous spaces, with little attention to dynamic, crowded environments.

By Yifei Dong, Fengyi Wu, Qi He, Lingdong Kong, Heng Li, Minghan Li, Zebang Cheng, Yuxuan Zhou, Jingdong Sun, Qi Dai, Alexander G Hauptmann, Zhi-Qi Cheng