Automated planning for robotic layup of composite prepreg. (February 2021)

• Record Type: Journal Article
• Authors: Malhan, Rishi K.; Shembekar, Aniruddha V.; Kabir, Ariyan M.; Bhatt, Prahar M.; Shah, Brual; Zanio, Scott; Nutt, Steven; Gupta, Satyandra K.
• Is Part Of: Robotics and computer-integrated manufacturing. Volume 67(2021)
• Publication Date: 2021-02
• Subjects: Composite automation -- Automated layup -- Robot base placement -- Grasp planning -- Multi-arm manipulation -- Path-constrained trajectory planning -- Industrial robots; Robots, Industrial -- Periodicals; Computer integrated manufacturing systems -- Periodicals; Robotics -- Periodicals; Robots industriels -- Périodiques; Productique -- Périodiques; Robotique -- Périodiques; 670.285
• DOI: 10.1016/j.rcim.2020.102020
• Languages: English
• ISSNs: 0736-5845

Abstract

Highlights: Automated grasp planning enables a multi-robot cell to determine where to grasp a ply during layup. Automated robot placement determines the location of the robots to execute complex constrained paths in the workspace. A physics-aware grasp planner and a successive application of constraints-based robot placement planner can handle complex industrial use cases. The robotic cell is capable of executing layup using the automatically generated plans. Abstract: Hand layup is a commonly used process for making composite structures from several plies of carbon-fiber prepreg. The process involves multiple human operators manipulating and conforming layers of prepreg to a mold. The manual layup process is ergonomically challenging, tedious, and limits throughput. Moreover, different operators may perform the process differently, and hence introduce inconsistency. We have developed a multi-robot cell to automate the layup process. A human expert provides a sequence to conform to the ply and types of end-effectors to be used as input to the system. The system automatically generates trajectories for the robots that can achieve the specified layup. Using the cell requires the automated generation of different types of plans. This paper addresses two main planning problems: (a) generating plans to grasp and manipulate the ply and (b) generating feasible robot trajectories. We use a hybrid-physics based simulator coupled with a state space search to find grasp plans. The system employs a strategy that applies constraints successively in a non-linear optimization formulation to identify suitable placements of the robots around the mold so that feasible trajectories can be generated. Our system can generate plans in a computationally efficient manner, and it can handle a wide variety of complex parts. We demonstrate the automated layup by conducting physical experiments on an industry-inspired mold using the generated plans.