eBots Inc. has secured a major milestone in manufacturing with a newly patented method for configuring robotic systems. This innovation focuses on their award-winning patent, titled ‘System and method for sequencing assembly tasks’. The patent describes a graphical interface and directed graph system designed to combat programming complexities that often lead to robotic configuration delays.

Revolutionizing Robotic Assembly

This outstanding invention has been awarded Swanson Reed’s Patent of the Month for February 2026 in the Manufacturing industry. It represents a significant leap forward in optimizing automated assembly lines and streamlining user-to-robot interactions.

Abstract

One embodiment can provide a method and system for configuring a robotic system. During operation, the system can present to a user on a graphical user interface an image of a work scene comprising a plurality of components and receive, from the user, a sequence of operation commands. A respective operation command can correspond to a pixel location in the image. For each operation command, the system can determine, based on the image, a task to be performed at a corresponding location in the work scene and generate a directed graph based on the received sequence of operation commands. Each node in the directed graph can correspond to a task, and each directed edge in the directed graph can correspond to a task-performing order, thereby facilitating the robotic system to perform a sequence of tasks based on the sequence of operation commands.

Meeting the U.S. R&D Tax Credit Rules

To qualify for the U.S. Research and Development (R&D) Tax Credit, technological developments must satisfy the IRS Four-Part Test. eBots Inc.’s development of this patent exemplifies these rules:

• Permitted Purpose: The research aimed to create a new, improved, and highly efficient process for configuring robotic systems, enhancing performance and reliability.
• Technological in Nature: The invention relies heavily on the principles of computer science, software engineering, and computer vision to map 2D pixel locations to 3D physical tasks and generate complex directed graphs.
• Elimination of Uncertainty: Engineers at eBots Inc. had to overcome technical uncertainties regarding how to accurately translate a user’s visual sequence commands into a functional, executable algorithmic order for a robotic arm without causing logic loops or physical collisions.
• Process of Experimentation: The team likely engaged in iterative testing of the graphical user interface, evaluating multiple algorithms for the directed graph generation, and simulating various work scenes to refine the accuracy of the pixel-to-task translations.

3 Practical Applications Qualifying for R&D

Companies attempting to implement or customize this patented technology in real-world environments would need to undertake significant developmental work. The following applications would likely involve qualifying R&D activities:

1. Automated Electronics Manufacturing: Adapting the pixel-to-task algorithm to recognize microscopic components on a printed circuit board (PCB). Engineers would need to experiment with the system’s precision, testing different high-resolution image processing speeds and sequencing algorithms to ensure robots place delicate, expensive parts without systematic errors.
2. Automotive Chassis Welding: Integrating the directed graph system into an automotive assembly line where the “work scene” involves large, complex 3D environments. R&D would be required to test and evaluate how the software handles branching or concurrent tasks (e.g., programming two robotic arms to weld simultaneously) while resolving technical uncertainties around sequencing order to prevent mechanical collisions.
3. Dynamic E-commerce Order Fulfillment: Customizing the software for a logistics center where components (packages) constantly vary in shape, weight, and barcode placement. Developers would undergo a process of experimentation to refine the GUI and task-generation logic so the robotic system can dynamically and rapidly adapt its pick-and-place sequence based on constantly changing images of a disorganized bin.