用环境约束提升软夹爪抓取纸类柔性材料的稳定性。
Introducing Environmental Constraints to Grasping Strategies for Paper-Like Flexible Materials Using a Soft Gripper
- 通过环境约束设计新型抓取策略，适配纸类材料特性。
- 实验验证不同材料与工况下抓取成功率和受力差异。
- 适合家用服务机器人抓取平面柔性物体场景。
机器人操作柔性物体在工业和服务领域广泛应用。其中，纸类材料相比布料更易受压应力影响，微小物理特性变化会显著影响抓取效果。本研究基于通用软夹爪，系统探究利用环境约束的抓取策略。结合现有抓取动作基元，提出一套利用环境约束的柔性材料抓取方法，并分析其力学与运动学模型。为评估材料属性和工作条件对抓取的影响，构建了测量抓取力与成功率的评价体系并进行实验验证。最终总结出不同策略适用的工作空间与特性，可满足多样化任务需求，推动家用服务机器人在平面柔性物体抓取中的应用。
原文摘要 · Abstract (English)
Robotic manipulation of flexible objects is widely required in both industrial and service applications. Among such objects, paper-like materials exhibit distinct mechanical characteristics compared to cloth, being more sensitive to compressive stress, where minor variations in physical properties can significantly affect grasping. This study systematically investigates grasping strategies for paper-like materials using a universal soft gripper by exploiting environmental constraints. Based on manipulation primitives employed in existing grasping strategies, we proposed systematic grasping strategies for flexible materials by exploiting environmental constraints and analyzed their mechanical and kinematic models. To investigate the influence of materials and working conditions on grasping, an evaluation system for measuring grasping force and success rate was defined and experimentally evaluated. Finally, we summarized the specific workspaces and characteristics of different strategies that can satisfy various task requirements and lead to potential applications in household service robots for grasping planar flexible objects.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。