Abstract: Various examples are provided related to face identification of material. An image can be captured by a vision system and feature parameters determined and compared to a material feature database to determine which face of the material is being presented. The vision system can employ a set of parameters for configuration to acquire the image. The system can communicate the identification to downstream processes in real time. A near-universal, color agnostic, angular orientation independent identification of material faces can be determined without the need for physical manipulation of the material.

Abstract: A sewn product making apparatus such as a sewing robot can be used to produce a variety of products over a broad range of sizes, shapes or materials. Various examples are provided related to the automation of sewing robots, and the making of sewn products. In one example, among others, a system can generate a product making path using a product construction file, and instruct a sewing device and fabric mover(s) to automatically sew the product based upon the product making path. The product making path can be modified when a deviation is detected, and the sewing adjusted based upon the modified product making path. The product construction file can be generated using information from a computer aided design associated with the product.

Abstract: Various examples are provided related to face identification of material. An image can be captured by a vision system and feature parameters determined and compared to a material feature database to determine which face of the material is being presented. The vision system can employ a set of parameters for configuration to acquire the image. The system can communicate the identification to downstream processes in real time. A near-universal, color agnostic, angular orientation independent identification of material faces can be determined without the need for physical manipulation of the material.

Abstract: Various examples are provided related to face identification of material. An image can be captured by a vision system and feature parameters determined and compared to a material feature database to determine which face of the material is being presented. The vision system can employ a set of parameters for configuration to acquire the image. The system can communicate the identification to downstream processes in real time. A near-universal, color agnostic, angular orientation independent identification of material faces can be determined without the need for physical manipulation of the material.

Abstract: A sewn product making apparatus such as a sewing robot can be used to produce a variety of products over a broad range of sizes, shapes or materials. Various examples are provided related to the automation of sewing robots, and the making of sewn products. In one example, among others, a system can generate a product making path using a product construction file, and instruct a sewing device and fabric mover(s) to automatically sew the product based upon the product making path. The product making path can be modified when a deviation is detected, and the sewing adjusted based upon the modified product making path. The product construction file can be generated using information from a computer aided design associated with the product.

Abstract: Due to rapid advancement in computing technology of both hardware and software, the labor intensive sewing process has been transformed into a technology-intensive automated process. During an automated process, product materials may become wrinkled or folded, which can slow down the automated process or result in human intervention. Various examples are provided related to the automation of sewing robots, and removal of wrinkles from products. Images of material on a work table can be captured and analyzed to determine if there are wrinkles or folds in the product. The robot can remove the wrinkle or fold by manipulating the material through the use of end effectors such as, e.g., budgers.

Abstract: Due to rapid advancement in computing technology of both hardware and software, the labor intensive sewing process has been transformed into a technology-intensive automated process. During an automated process, product materials may become wrinkled or folded, which can slow down the automated process or result in human intervention. Various examples are provided related to the automation of sewing robots, and removal of wrinkles from products. Images of material on a work table can be captured and analyzed to determine if there are wrinkles or folds in the product. The robot can remove the wrinkle or fold by manipulating the material through the use of end effectors such as, e.g., budgers.

Abstract: A sewn product making apparatus such as a sewing robot can be used to produce a variety of products over a broad range of sizes, shapes or materials. Various examples are provided related to the automation of sewing robots, and the making of sewn products. In one example, among others, a system can generate a product making path using a product construction file, and instruct a sewing device and fabric mover(s) to automatically sew the product based upon the product making path. The product making path can be modified when a deviation is detected, and the sewing adjusted based upon the modified product making path. The product construction file can be generated using information from a computer aided design associated with the product.

Abstract: Due to rapid advancement in computing technology of both hardware and software, the labor intensive sewing process has been transformed into a technology-intensive automated process. During an automated process, processing of a work piece can be visually monitored using a sensor system. Data gathered from the sensor system can be used to infer the condition and/or position of the work piece in the work area using, e.g., models of a sensor profile. Evaluation can be carried out before processing begins, during processing and/or after processing of the work piece. Examples of systems and methods are described that provide for initially and successively matching the model of the expected shape for a product work piece to a set of sensor readings of the work piece in order to determine the position of the work piece and support a variety of useful features.

Abstract: Due to rapid advancement in computing technology of both hardware and software, the labor intensive sewing process has been transformed into a technology-intensive automated process. During an automated process, product materials may become wrinkled or folded, which can slow down the automated process or result in human intervention. Various examples are provided related to the automation of sewing robots, and removal of wrinkles from products. Images of material on a work table can be captured and analyzed to determine if there are wrinkles or folds in the product. The robot can remove the wrinkle or fold by manipulating the material through the use of end effectors such as, e.g., budgers.

Abstract: Due to rapid advancement in computing technology of both hardware and software, the labor intensive sewing process has been transformed into a technology-intensive automated process. During an automated process, processing of a work piece can be visually monitored using a sensor system. Data gathered from the sensor system can be used to infer the condition and/or position of the work piece in the work area using, e.g., models of a sensor profile. Evaluation can be carried out before processing begins, during processing and/or after processing of the work piece. Examples of systems and methods are described that provide for initially and successively matching the model of the expected shape for a product work piece to a set of sensor readings of the work piece in order to determine the position of the work piece and support a variety of useful features.

Abstract: A sewn product making apparatus such as a sewing robot can be used to produce a variety of products over a broad range of sizes, shapes or materials. Various examples are provided related to the automation of sewing robots, and the making of sewn products. In one example, among others, a system can generate a product making path using a product construction file, and instruct a sewing device and fabric mover(s) to automatically sew the product based upon the product making path. The product making path can be modified when a deviation is detected, and the sewing adjusted based upon the modified product making path. The product construction file can be generated using information from a computer aided design associated with the product.