About this Abstract |
| Meeting |
2026 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2026)
|
| Symposium
|
2026 Annual International Solid Freeform Fabrication Symposium (SFF Symp 2026)
|
| Presentation Title |
Collision-Aware Topology Optimization (CATO) for Robotic-Enabled Additive Manufacturing |
| Author(s) |
Conner Petru, Ronnie Stone, Arya Haria, Zhenghui Sha |
| On-Site Speaker (Planned) |
Conner Petru |
| Abstract Scope |
Topology optimization (TO) is a method for generating designs that satisfy constraints while pursuing specific objectives (e.g., minimizing weight). Existing TO workflows typically focus on structural performance and manufacturability for traditional 3D printing, disregarding robot-enabled AM and assembly. As a result, many automated tasks still require human intervention. One such scenario is robotic arm-enabled FDM, which introduces complex kinematics and collision geometries generally not considered in TO. This requires a TO framework that not only adapts to the component’s fabrication process (e.g., additive), but also to its automation environment. This paper introduces Collision-Aware Topology Optimization (CATO) for Robotic-Enabled Additive Manufacturing, a new TO pipeline that incorporates ROS-based collision feedback to ensure that the generated design can be feasibly manufactured and assembled using robotic arms. By analyzing the performance of this pipeline for robotic-enabled fabrication tasks, we investigate how TO can leverage simulation feedback for future autonomous factories. |
| Proceedings Inclusion? |
Undecided |