Abstract: Robots might interact with planar objects (e.g., garments) for process automation, quality control, to perform sewing operations, or the like. It is recognized herein that robots interacting with such planar objects can pose particular problems, for instance problems related to detecting the planar object and estimating the pose of the detected planar object. A system can be configured to detect or segment planar objects, such as garments. The system can include a three-dimensional (3D) sensor positioned to detect a planar object along a transverse direction. The system can further include a first surface that supports the planar object. The first surface can be positioned such that the planar object is disposed between the first surface and the 3D sensor along the transverse direction. In various examples, the 3D sensor is configured to detect the planar object without detecting the first surface.

Abstract: A method for automatically generating a bill of process in a manufacturing system comprising: receiving design information representative of a product to be produced; iteratively performing simulations of the manufacturing system; identifying manufacturing actions based on the simulations; optimizing the identified manufacturing actions to efficiently produce the product to be produced; generating, by the manufacturing system, a bill of process for producing the product. Simulations may be performed using a digital twin of the product being produced and a digital twin of the environment. System actions are optimized using a reinforcement learning technique to automatically produce a bill of process based on the design information of the product and task specifications.

Abstract: A computer-implemented method for designing execution of a process by a robotic cell includes obtaining a process goal and one or more process constraints. The method includes accessing a library of constructs and a library of skills. Each construct includes a digital representation of a component of the robotic cell or a geometric transformation of the robotic cell. Each skill includes a functional description for using a robot of the robotic cell to interact with a physical environment to perform a skill objective. The method uses a simulation engine to simulate a multiplicity of designs, wherein each design is characterized by a combination of constructs and skills to achieve the process goal, and determine a set of feasible designs that meet the one or more process constraints. The method includes outputting recommended designs from the set of feasible designs.