{"slug": "obstadiff-generalizable-diffusion-policy-learning-via-obstacle-aware", "title": "ObstaDiff: Generalizable Diffusion Policy Learning via Obstacle-aware Representations", "summary": "ObstaDiff, a decomposed diffusion-policy framework with a lightweight obstacle-aware visual encoder, achieved 75.41% average task success and an 8.20% average obstacle collision rate across 61 real-robot greenhouse trials per method, totaling 366 executions, according to the arXiv paper 2609.10918v1. The framework extracts a structured target-obstacle-background representation so a downstream alignment policy can generate end-effector trajectories toward a target-centered bottleneck pose while reasoning about surrounding obstacles. ObstaDiff outperformed representative imitation-learning baselines and improved generalization in cluttered agricultural scenes.", "body_md": "arXiv:2609.10918v1 Announce Type: cross \nAbstract: Imitation learning has achieved impressive results in robotic manipulation, yet most existing approaches assume clean backgrounds and lack explicit mechanisms for obstacle-aware motion generation. Extending such policies to cluttered, real-world scenes with unstructured obstacles remains a key generalization challenge. We present ObstaDiff, a decomposed diffusion-policy framework with a lightweight obstacle-aware visual encoder. ObstaDiff extracts a structured target-obstacle-background representation, enabling the downstream alignment policy to generate end-effector trajectories toward a target-centered bottleneck pose while reasoning about surrounding obstacles. We evaluate ObstaDiff on 61 real-robot greenhouse trials per method (366 executions in total). ObstaDiff achieves 75.41% average task success and 8.20% average obstacle collision rate, outperforming representative imitation-learning baselines and improving generalization in cluttered agricultural scenes.", "url": "https://wpnews.pro/news/obstadiff-generalizable-diffusion-policy-learning-via-obstacle-aware", "canonical_source": "https://www.machinebrief.com/news/obstadiff-generalizable-diffusion-policy-learning-via-obstac-ile2", "published_at": "2026-09-11 04:00:00+00:00", "updated_at": "2026-09-11 05:27:31.137933+00:00", "lang": "en", "topics": ["robotics", "machine-learning", "computer-vision", "ai-research"], "entities": ["ObstaDiff", "arXiv"], "alternates": {"html": "https://wpnews.pro/news/obstadiff-generalizable-diffusion-policy-learning-via-obstacle-aware", "markdown": "https://wpnews.pro/news/obstadiff-generalizable-diffusion-policy-learning-via-obstacle-aware.md", "text": "https://wpnews.pro/news/obstadiff-generalizable-diffusion-policy-learning-via-obstacle-aware.txt", "jsonld": "https://wpnews.pro/news/obstadiff-generalizable-diffusion-policy-learning-via-obstacle-aware.jsonld"}}