运动学
模块化设计
机械臂
机器人
可扩展性
工程类
接口(物质)
计算机科学
灵活性(工程)
模拟
反向动力学
正向运动学
控制工程
机械工程
人工智能
物理
经典力学
数据库
操作系统
统计
数学
肺表面活性物质
吉布斯等温线
化学工程
作者
Virgilio Gómez,Miguel Hernando,Esther Aguado,Daniel Bajo,Cláudio Rossi
出处
期刊:Soft robotics
[Mary Ann Liebert]
日期:2024-04-01
卷期号:11 (2): 347-360
被引量:1
标识
DOI:10.1089/soro.2023.0020
摘要
In recent years, the development of mining robots has grown significantly, offering improved efficiency and safety in hazardous environments. However, there is still room for improvement in adaptability, scalability, and overall performance. The ROBOMINERS project, funded by the European Union's Horizon 2020 Research and Innovation Program, aims to facilitate Europe's access to mineral resources applying disruptive robotic concepts. One such concept is resilience, which can be achieved providing modular mining robots with the ability to reconfigure during operation. To address this challenge, this article presents the development and kinematic modeling of a soft, telescopic, continuum arm integrated into a modular robot. The arm serves as a mechanical interface for coupling different robotic modules or tools following the principle of the car crane. With a fully 3D-printed design, the arm features two sections of variable length that are driven by an innovative actuation method based on soft racks. It provides a 6 degrees of freedom (DoF) motion. The arm kinematic models are obtained by backbone parameterization assuming constant curvature and independent bending between sections for forward kinematics and applying a machine learning-based approach for inverse kinematics. The models are validated through the evaluation of two trajectories, measuring the deviation in each DoF and rack extension. Furthermore, a demonstration of the arm's coupling procedure between two robotic modules and one possible configuration of the robotic system showcases its functionality.
科研通智能强力驱动
Strongly Powered by AbleSci AI