Pre-recorded Sessions: From 4 December 2020 | Live Sessions: 10 – 13 December 2020
4 – 13 December 2020
Pre-recorded Sessions: From 4 December 2020 | Live Sessions: 10 – 13 December 2020
4 – 13 December 2020
#SIGGRAPHAsia | #SIGGRAPHAsia2020
#SIGGRAPHAsia | #SIGGRAPHAsia2020
Date/Time:
04 – 13 December 2020
All presentations are available in the virtual platform on-demand.
Lecturer(s):
Ali Mahdavi Amiri, Simon Fraser University, Canada
Fenggen Yu, Simon Fraser University, Canada
Haisen Zhao, University of Washington, Shandong University, United States of America
Adriana Schulz, University of Washington, United States of America
Hao (Richard) Zhang, Simon Fraser University, Canada
Bio:
Description: We introduce carvable volume decomposition for efficient 3-axis CNC machining of 3D freeform objects, where our goal is to develop a fully automatic method to jointly optimize setup and path planning. We formulate our joint optimization as a volume decomposition problem which prioritizes minimizing the number of setup directions while striving for a minimum number of continuously carvable volumes, where a 3D volume is continuously carvable, or simply carvable, if it can be carved with the machine cutter traversing a single continuous path. Geometrically, carvability combines visibility and monotonicity and presents a new shape property which had not been studied before. Given a target 3D shape and the initial material block, our algorithm first finds the minimum number of carving directions by solving a set cover problem. Specifically, we analyze cutter accessibility and select the carving directions based on an assessment of how likely they would lead to a small carvable volume decomposition. Next, to obtain a minimum decomposition based on the selected carving directions efficiently, we narrow down the solution search by focusing on a special kind of points in the residual volume, single access or SA points, which are points that can be accessed from one and only one of the selected carving directions. Candidate carvable volumes are grown starting from the SA points. Finally, we devise an energy term to evaluate the carvable volumes and their combinations, leading to the final decomposition. We demonstrate the performance of our decomposition algorithm on a variety of 2D and 3D examples and evaluate it against the ground truth, where possible, and solutions provided by human experts. Physically machined models are produced where each carvable volume is continuously carved following a connected Fermat spiral toolpath.