Robotic Manipulation of Rods and Plates

Who is working on this project: Dezhong Tong

Project: Helix Instability

We report an automatic experimental setup based on robots to study the instability of a rod with a helical centerline.  Experimental analysis of the mechanics of a deformable object, and particularly its stability, requires repetitive testing and, depending on the complexity of the object's shape, a testing setup that can manipulate many degrees of freedom at the object's boundary. Traditional experimental setups, which are restricted for their limited automation and finite dexterity, are not applicable for studying the mechanics of deformable objects with complicated topologies. Motivated by recent advancements in robotic manipulation of deformable objects, we introduced robotic system in the experimental mechanics -- constructing a method for automated stability testing of a slender elastic rod, which is a canonical example of a deformable object. We focused on the rod with helical centerline in this projects since exciting bifurcations are observed as the helical configurations evolute. By implementing a recent geometric characterization of stability for helical rods, we developed a manipulation scheme to explore the space of stable helices. The vision system is developed to detect the onset of instabilities.  The experimental results obtained by our automated testing system show good agreement with numerical simulations of elastic rods in helical configurations. The methods described in this paper lay the groundwork for automation to grow within the field of experimental mechanics.

Publication: Tong, D., Borum, A. and Jawed, M.K., 2021. Automated stability testing of elastic rods with helical centerlines using a robotic system. IEEE Robotics and Automation Letters, 7(2), pp.1126-1133. [Link]

Funding: We are grateful for the financial support from the National Science Foundation under Grant Numbers IIS-1925360, CAREER-2047663, and CMMI-2101751.

Project: Robotic origami - folding a paper

Origami, the art of paper folding, is a process to construct different sculptures by creating designed creases on a paper pattern. In this project, we proposed an approach to create an arbitrary crease in the paper with two robots' collaborations. Since paper is a type of deformable objects, robot must be able to predict deformations of paper and capture the characteristic of permanent deformations -- crease -- during the manipulation process. In this work, we implements numerical simulation and mechanical analysis to develop a simplified model which can capture the mechanical responses of folding paper with sufficient accuracy and efficiency. A straightforward optimal controlling scheme, which can be translated to the robotic system easily, is generated through a data-driven approach. Due to the high computation efficiency of the controlling scheme, we combine it with perception system to construct a feed-back control policy. Our work shows the performance of the physics-training solution for robotic origami.

Figure: TBD

Publication: TBD

Funding: We are grateful for the financial support from the National Science Foundation under Grant Numbers IIS-1925360, CAREER-2047663, and CMMI-2101751.

Github: N/A

YouTube: TBD

Project: Robotic rope deployment

In this project, we propose a mechanics-based approach to study how to deploy a rope into prescribed pattern on the rigid substrate. Rope deployment is one of the process of interaction between soft matters and solid objects, which plays significant roles in engineering, e.g., deployment of marine cables. In this project, we combine numerical simulations, scaling analysis, and robotic system to study the process of rope deployment. We study the physics of this process and find the global optima to do the rope deployment. A optimal deployment approach which is able to deploy a rope along a prescribed pattern accurately is computed. With this method, sliding is minimized to keep the pattern on the substrate stable. Robotic experiments are also demonstrated with good agreement with simulations.

Figure: TBD

Publication: TBD

Funding: We are grateful for the financial support from the National Science Foundation under Grant Numbers IIS-1925360, CAREER-2047663, and CMMI-2101751.

Github: TBD

YouTube: TBD