arXiv cs.AI· Mariano Ram\'irez Montero, Ebrahim Shahabi, Giovanni Franzese, Jens Kober, Barbara Mazzolai, Cosimo Della Santina·· 10 小时前AI 评分31
混合软硬机器人系统结合模仿学习实现超越刚性操作的灵巧任务
Learning Beyond Rigid Manipulation with Hybrid Soft-Rigid Robots
AI 导读
研究者构建了刚性机械臂与软体机械臂串联的混合机器人系统，并提出一种可通用适配此类混合系统的模仿学习算法，利用刚性精度与软体柔顺性的互补优势习得操作技能，并能在任务变化中单次泛化。该系统在堆叠等经典任务上达到或超过刚性机器人表现，还能完成穿过狭窄开口抓取物体等此前无法实现的新行为。
正文 · 原文
Abstract:Rigid-soft robot hybrids promise to unite the precision and repeatability of rigid manipulators with the compliance and adaptability of soft structures. Yet, full-fledged rigid-soft manipulators remain largely unexplored, in part because the intelligence required to exploit this combination is still missing. Here, we introduce a hybrid robotic system obtained by the series interconnection of a rigid arm and a soft manipulator, and systematically examine its ability to perform both established and previously inaccessible manipulation tasks. We show that a tailored imitation learning algorithm -- generally applicable to this class of hybrid systems -- leverages the complementary roles of rigid precision and soft embodiment to acquire manipulation skills and generalize them in a single shot across task variations. As a result, the system matches or exceeds the performance of rigid robots in classical tasks such as stacking, while enabling qualitatively new behaviors, including grasping objects through narrow openings.
| Comments: | Revised version with new title, abstract, and experiments |
| Subjects: | Robotics (cs.RO); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2410.07787 [cs.RO] |
| (or arXiv:2410.07787v4 [cs.RO] for this version) | |
| https://doi.org/10.48550/arXiv.2410.07787 arXiv-issued DOI via DataCite |
Submission history
From: Cosimo Della Santina [view email]
[v1]
Thu, 10 Oct 2024 10:18:03 UTC (26,071 KB)
[v2]
Fri, 11 Oct 2024 11:41:00 UTC (26,072 KB)
[v3]
Wed, 5 Nov 2025 12:35:08 UTC (25,736 KB)
[v4]
Mon, 9 Nov 2026 20:53:39 UTC (5,191 KB)
来源：arXiv cs.AI · arxiv.org