Applying Deep Reinforcement Learning to Cable Driven Parallel Robots for Balancing Unstable Loads: A Ball Case Study.

ABSTRACT: The current pandemic has highlighted the need for rapid construction of structures to treat patients and ensure manufacturing of health care products such as vaccines. In order to achieve this, rapid transportation of construction materials from staging area to deposition is needed. In the future, this could be achieved through automated construction sites that make use of robots. Toward this, in this paper a cable driven parallel manipulator (CDPM) is designed and built to balance a highly unstable load, a ball plate system. The system consists of eight cables attached to the end effector plate that can be extended or retracted to actuate movement of the plate. The hardware for the system was designed and built utilizing modern manufacturing processes. A camera system was designed using i

SUBMITTER: Grimshaw A 

PROVIDER: S-EPMC7938313 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature