{
  "id": 1132,
  "url": "https://arxiv.org/abs/2606.12603v1",
  "title": "From Imitation to Alignment: Human-Preference Flow Policies for Long-Horizon Sidewalk Navigation",
  "summary": "Autonomous long-horizon sidewalk navigation is essential for micro-mobility applications such as robotic food delivery and assistive electronic wheelchairs. Unlike autonomous driving on the road, long-horizon sidewalk navigation requires precise maneuvering through unpredictable sidewalk terrains and pedestrians, with a lightweight perception stack as minimal as a single monocular RGB camera. While imitation learning (IL) from demonstrations offers a practical solution, the resulting autopilot p",
  "authors": "Honglin He, Zhizheng Liu, Yukai Ma, Bolei Zhou",
  "category": "research",
  "topics": "safety-alignment,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-06-10T19:01:31.000Z",
  "fetched_at": "2026-07-14T14:15:03.615Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/1132",
  "original_url": "https://arxiv.org/abs/2606.12603v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}