Summary Report on Mini-Sabbatical: Fall 1994

Ken Goldberg

During September-December 1994, I pursued research in Manufacturing at three institutions in the Bay Area: Adept Technology, Inc., UC Berkeley, and Silma, Inc. For the first 2 months I lived in a trailer on John Craig's ranch near San Jose and wrote code on a solar powered SGI Extreme; for the latter 2 months I lived in Pacific Heights and commuted to Berkeley. I also made several visits to Jean-Claude Latombe's lab at Stanford.

My primary objective, funded by Adept Technology, was to transfer geometric algorithms to Silma's new simulation package that will be used to facilitate Rapid Deployment Automation (see below). I worked closely with John Craig to learn Silma's proprietary language, Sil, and theit new user interface, called RAPID.

I focused on modelling Adept's Flexible Part Feeder. This feeder singulates parts by causing them to drop from one conveyor belt to another. To model how the feeder will perform over repeated cycles with a given part, it is important to predict the statistical distribution of stable poses as that part is randomly dropped.

In 1992, my group developed an efficient algorithm for this problem (Computing a Statistical Distribution of Stable Poses for a Polyhedron, A. Rao, J. Wiegley and K. Goldberg, 30th Annual Allerton Conference on Communications, Control and Computing, University of Illinois, September, 1992). Versions of this algorithm were implemented by my students at USC: Wiegley in 1992, Zheng Yeh in 1993, and Yan Zhuang in 1994.

In fall 1994, I implemented the algorithm in Sil. The input is a CAD model of the part to be fed (we restrict attention to the polygonal convex hull of such parts) and the part's center of mass. The output is all stable poses of the part: For each, the estimated probability that the part will fall onto this pose. Combined with timing estimates for arm motion and camera cycle time, pose statistics allow us to estimate how often the part can be picked up vs. recycled through the feeder. The analysis is quasi-static in that it does not consider the dynamics of collisions or friction.

Once the algorithm was running in Sil, John Craig integrated it into RAPID. Initially, we estimated probabilities for the class of random parts generated by extruding random convex hulls. Next, we extended the algorithm to handle general parts and estimated probabilities for four industrial parts: an orange insulator cap used in previous experiments, a camera shell from Kodak, and two cluster gears from Johnson Controls. Rob Zanutta of Adept ran a batch of insulator caps and Kodak parts through Adept's flexible part feeder to compare actual with predicted statistics. Note that the algorithm assumes that each part drops in isolation while in the feeder parts drop in bulk.

Orange insulator cap (1036 trials)

Pose(Predicted)Measured
1(7 %)2.22 %
2(9 %)5.02 %
3(20 %)19.69 %
4(32 %)27.12 %
5(32 %)45.95 %

The distribution compares reasonably well with the exception of pose 5, which occurs 14% more frequently than predicted. This is the most stable pose in terms of potential energy, so it is understandable that kinetic energy might shift the distribution toward this pose

Black Kodak Camera Shell (627 trials)

Pose(Predicted)Measured
1 (40 %)52.5 %
2 (14 %)4.5 %
3 (7 %)1.9 %
4 (32 %)39.4 %
5 (7 %)1.6 %

As Rob noted, poses 3 and 5 were susceptible to toppling due to inter-part collisions and belt motion.

Other developments:

I would like to thank everyone who helped make this Sabbatical possible and so rewarding. In particular, I owe a great debt to Brian Carlise and John Craig for including me in a project that has tremendous potential for Robotics in this country, and to John Canny and Jean-Claude Latombe for sharing their thoughts, computers, office space, outstanding students and post-docs. I have the utmost respect for these four and am lucky to count them as friends.

I would also like to thank Ellis Horowitz of USC for informing me of the possibility for taking a mini-sabbatical, and Howard Moraff from NSF and Dean Len Silverman and the faculty of the USC Computer Science Department for their encouragement. I'd also like to thank my students at USC for not playing too much while the cat was away, and my assistant Delsa Tan for reading my mail and answering a series of panicky requests from afar. And thanks to my family in the area including Adele, Ali, Nina, Jim, David, and Rose; and to my old friends Jonny and Margaret (and now Caitlin), Pammy Aranow, Scott Balcerek, Kristina Robinson, Ovid Jacob, Danny Halperin, Bruce Donald, and the many new friends I made: Max Mendel, Jenny Cool, Tania Miller, Zane Vella, Ann Hess, Chris Vietor, and especially Eric Paulos, who showed me all the great places to drink coffee and talk about machines.

(Ken Goldberg, 2 January, 1995, San Francisco, CA)


goldberg@cs.usc.edu