Model-Based Manipulation of Linear Flexible Objects: Task Automation in Simulation and Real World†

被引:17
作者
Chang, Peng [1 ]
Padir, Taskin [2 ]
机构
[1] Northeastern Univ, Dept Elect & Comp Engn, Boston, MA 02115 USA
[2] Northeastern Univ, Inst Experiential Robot, Boston, MA 02115 USA
基金
美国国家科学基金会; 美国国家航空航天局;
关键词
flexible object manipulation; intelligent robotic system; modeling of flexible objects; task automation; Sim2Real; perception for grasping and manipulation; visual servoing; ROBOTS;
D O I
10.3390/machines8030046
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Manipulation of deformable objects is a desired skill in making robots ubiquitous in manufacturing, service, healthcare, and security. Common deformable objects (e.g., wires, clothes, bed sheets, etc.) are significantly more difficult to model than rigid objects. In this research, we contribute to the model-based manipulation of linear flexible objects such as cables. We propose a 3D geometric model of the linear flexible object that is subject to gravity and a physical model with multiple links connected by revolute joints and identified model parameters. These models enable task automation in manipulating linear flexible objects both in simulation and real world. To bridge the gap between simulation and real world and build a close-to-reality simulation of flexible objects, we propose a new strategy called Simulation-to-Real-to-Simulation (Sim2Real2Sim). We demonstrate the feasibility of our approach by completing the Plug Task used in the 2015 DARPA Robotics Challenge Finals both in simulation and real world, which involves unplugging a power cable from one socket and plugging it into another. Numerical experiments are implemented to validate our approach.
引用
收藏
页数:22
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