{"ID":2865696,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.20646","arxiv_id":"2509.20646","title":"Suction Leap-Hand: Suction Cups on a Multi-fingered Hand Enable Embodied Dexterity and In-Hand Teleoperation","abstract":"Dexterous in-hand manipulation remains a foundational challenge in robotics, with progress often constrained by the prevailing paradigm of imitating the human hand. This anthropomorphic approach creates two critical barriers: 1) it limits robotic capabilities to tasks humans can already perform, and 2) it makes data collection for learning-based methods exceedingly difficult. Both challenges are caused by traditional force-closure which requires coordinating complex, multi-point contacts based on friction, normal force, and gravity to grasp an object. This makes teleoperated demonstrations unstable and amplifies the sim-to-real gap for reinforcement learning. In this work, we propose a paradigm shift: moving away from replicating human mechanics toward the design of novel robotic embodiments. We introduce the \\textbf{S}uction \\textbf{Leap}-Hand (SLeap Hand), a multi-fingered hand featuring integrated fingertip suction cups that realize a new form of suction-enabled dexterity. By replacing complex force-closure grasps with stable, single-point adhesion, our design fundamentally simplifies in-hand teleoperation and facilitates the collection of high-quality demonstration data. More importantly, this suction-based embodiment unlocks a new class of dexterous skills that are difficult or even impossible for the human hand, such as one-handed paper cutting and in-hand writing. Our work demonstrates that by moving beyond anthropomorphic constraints, novel embodiments can not only lower the barrier for collecting robust manipulation data but also enable the stable, single-handed completion of tasks that would typically require two human hands. Our webpage is https://sites.google.com/view/sleaphand.","short_abstract":"Dexterous in-hand manipulation remains a foundational challenge in robotics, with progress often constrained by the prevailing paradigm of imitating the human hand. This anthropomorphic approach creates two critical barriers: 1) it limits robotic capabilities to tasks humans can already perform, and 2) it makes data co...","url_abs":"https://arxiv.org/abs/2509.20646","url_pdf":"https://arxiv.org/pdf/2509.20646v1","authors":"[\"Sun Zhaole\",\"Xiaofeng Mao\",\"Jihong Zhu\",\"Yuanlong Zhang\",\"Robert B. Fisher\"]","published":"2025-09-25T01:05:34Z","proceeding":"cs.RO","tasks":"[\"cs.RO\"]","methods":"[\"Reinforcement Learning\"]","project_urls":"[\"https://sites.google.com/view/sleaphand\"]","has_code":false,"code_links":[{"ID":609296,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2865696,"paper_url":"https://arxiv.org/abs/2509.20646","paper_title":"Suction Leap-Hand: Suction Cups on a Multi-fingered Hand Enable Embodied Dexterity and In-Hand Teleoperation","repo_url":"https://github.com/google/safevalues","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}