3D layout planning for robotic workcells with task-aware motion optimization: Generalization and real implementation

The design of robotic workcell layouts is pivotal for optimizing manufacturing efficiency by ensuring effective space utilization and seamless task execution. Traditional 2D layout planning approaches often fall short in addressing practical implementation challenges, such as task feasibility and motion constraints. This paper introduces a generalized 3D workcell layout planning framework that integrates robotic task and motion planning into the layout planning optimization process. The framework employs component CAD models, workcell dimensions, and robot task specifications to automate layout generation. A hybrid optimization algorithm minimizes space occupation and operation time while ensuring task-specific constraints are met. Grasp pose analysis and motion planning further enhance the feasibility of the manipulation task. Validation was conducted through simulations across various workcell configurations, including multi-robot systems, and a practical implementation experiment was performed to demonstrate real-world applicability. Results demonstrated layouts that reduced space utilization by 94% from the initial design, ensuring successful execution of manipulation tasks and achieving solutions within an average of 12 minutes. This research bridges the gap between layout optimization and task execution by introducing a generalized, task-aware framework that incorporates 3D-enabled design, practical implementation, and grasp-constrained scheduling for advanced manufacturing systems.