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I found some good papers on minimization techniques
[https://www.cs.cmu.edu/~quake-papers/painless-conjugate-gradient.pdf] An Introduction to the Conjugate Gradient Method Without the Agonizing Pain
[http://andrew.gibiansky.com/blog/machine-learning/hessian-free-optimization/] Hessian Free Optimization
These lessons are derived from working towards the Amazon Picking Challenge (APC) between September 2015 and June 2016. I had an opportunity to interact with other teams during the final competition at RoboCup, Leipzig, Germany.
Our system consisted of modules for perception, grasping and motion planning tied together using ROS and smash state controller. I think our strength was in the simplicity of system.
Software Codebase
Should have sat down and written a list of software rules. Code reviews not abusing ros - we used it everywhere more wellthough out architecture, naming conventions Lesser ros. More cpp. Code freeze 1 month before UBonn - Nimbro team had nice software. They had some superb rqt plugins which would have made testing a lot easier. Lot of prior robocup soccer experience
Testing
Better testing architecture. Like really solid. Break down into smaller components. Decide interface. Test independently. integration would have been awesome
In our case we had a perception, planning and grasping. Should have built enough infra code for testing: trajectory
introspection tool
Better state machine.
Motion Planning better caching infra, better planning speed
focus on score before hand - read into competition rule. Better to get 8 than all and fail.
// add stuff from notes
no team used in bin collision checking. Convex hull for detecting collisions. faster
Robots & Actuators
Early on, we made a decision to switch from the PR2 (which was already available to us) to a UR5. The PR2 had a moving base and a telescopic spine - these would have made planning more complex and slower. Universal Robots loaned us a UR5.
The UR5 was an amazing robot - it had tight ROS integration and was force compliant. We were up and running in no time.
However, with the UR5, we had reachability issues - We could not easily plan paths to the corners of all the shelf bins as our end-effector greatly limited workspace. At the competition, we were the only team using the UR5. Many of the other teams had a UR10 robot with a linearly actuated arm - resulting in a much larger workspace, better reachability and easier planning. Next time, UR10 with a linearly actuated arm would be the way to go!
End effector
Due to the task, items and grasping complexity, most APC teams prefer to use suction grasping end-effectors. This obviates the need for accurate perception and force-closure for finger grasping.
The MIT team’s end-effector was unique and large - it had grasping arms and suction. The Delft teams’ was more elegant - suction and a clamp. These would have enabled them to grasp even the 3lb dumbbell and black mesh pencil cup.
Should not have finalized and put the end-effector design on hold. We saw a lot of teams having smaller suction cups. Better suction system.
We used pretty basic electronics - Arduino, AC relays, pressure sensors and a linear actuator.
Perception
The top teams had a lighting setup mounted inside their workspace. This allows them better control for using CNNs for item identification. It would also allow them to transform the perception data to match lighting conditions of their training data set.
We were probably the only team using the bulky Kinect 2. Most teams used a smaller Creative Auto or Intel Realsense 3D sensors. A smaller sensor mounted on our arm would have allowed us to mount multiple sensors, giving better recongition. Would have also made in-bin planning much easier.
A huge drawback was that Kinect2 used time of flight technology compared to the other Structured Light sensors. // put links. The Halogens lamps mounted on the ceiling emitted IR radiation which interfered with our sensors and they had to be removed. Most teams used creative. Halogen Lamps
multiple images - We should have taken multiple images of the items in the bin, giving us better recognition.
Other Lessons
Better planning for transportation - If anything goes wrong, it will cause stress and in our hurry, we would overloop some other important factor. Me forgetting about transformer is a good example.
Teams - this is the first time I’m working in a 5-person team for extended periods of time.
Balancing coursework, research and projects is pretty hard. I could really improve my time management.
packing - send things before. more thought. Things which will not work
worked with awesome team. Learnt a bit of mech and factors that go into designing things. Prototyping. programming funda.
Engineering workflow - I realized that the MRSD project course was structured very similar to the workflow in an actual company.
Amazon Picking Challenge is a competition for designing a robot system to complement Amazon’s Kiva shelf system in warehouses. The workspace consists of a 12-bin shelf and a storage box. Each shelf bin can have multiple items placed in any configure with partial occlusions. A task list is provided of the required items. The goal is to pick the correct item from the bin and place it in the storage box.
As a part of MRSD course project, our 5-person team worked on the project from September 2015 to May 2016. You can see our course project webpage at http://mrsdprojects.ri.cmu.edu/2015teamd/. During this period, we designed the system from the ground up.
We were mentored by Prof. Maxim from the Search Based Planning Lab at CMU. We intially developed the system on a Willow Garage PR2 robot but found its reachability too poor for our task - in order to reach all the regions in our shelf, we would have had to change the spine height and move the robot, both of which would have added a layer of complexity in planning and increased time. Universal Robots was kind enough to lend us a UR5 arm. Migrating our code to the UR5 was a breeze. We were super psyched when we were shortlisted as finalists sometime in February 2016.
During summer, 3 members of our team started their internships in California. We would work on this project in the evenings after work and during weekends.
Day -1: June 27
We disassembled and packaged the robot, mounting frame, controller, items and the two computers. It was 450lbs between 4 of us. We had decided to take the robot as a check-in luggage instead of shipping it before as it would buy us more development time.
Day 0: June 28
We were scheduled to fly out of Pittsburgh in the afternoon and reach Berlin on June 29, just in time for the robot setup and testing day. As Murphy’s law would have it, our connecting flight to Newark got cancelled twice due to ATC issues. We spent the night camping at the airport as the next available flight was in the morning.
Fort HARP!
Day 1: June 29
Spent in airports and air. Our quickest route to Berlin was to fly backwards to Chicago, go to Frankfurt and then to Berlin. We were super concerned about our robot cargo not making it on time.
Day 2: June 30
We finally landed in Berlin! We were delayed by 28 hours. We rented a Peugot and raced to Leipzig on the Autobahn. Rick and Bhatia had already got there before us.
Today was the practice run day where we get and item arrangement closest to the competition - a mock competition.We saw a lot of teams tweaking their perception system to adjust to the warehouse lighting.
We turn up at the conference venue and frantically unpacked and setup our robot. Much to our chagrin, we found our computer cases smashed with dangling CPU cooler, RAM and the power supply cables. Thankfully, we could patch it up enough.
Then our linear actuator wasn’t being powered properly, our linear power supply wasn’t working and our shop-vac suction system was super loud. Power supply conked. Then we realized we were powering 110VAC 60hz equipment with 240VAC 50Hz. In my hurry, I mistook the power junction box to be a 110VAC-240VAC. We had to run out and get a new Shop-vac. We then rigged a power source for the linear actuator using a drill battery!
Kinect was giving very noisy pointclouds. Later we learnt it was due to the Halogen lamps which emit IR. Our Kinect was 2 - using Time of Flight instead of structured light which was more immune.
Day 3: July 1st
Stow task finals
We finally got it up and running. //pic
Due to an error, we were giving the wrong JSON file. So we had to run twice. First time, we stowed 7 items we got 88. Second item, we stored 8 items but misidentified one, fetching us 77.
We were placed 6th in the stowage competiton out of the 16 finalists.
// talk about our performance and other teams
Delft did really well. They were done and had 6 minutes to spare.
// pic - show our system // pic - show final scores?
Day 4: July 2nd
Picking task finals // talk about our performance and other teams
We made a decision to modify logic for certain items in fear of dropping. We had a lot of time and were looping between 2 shelves. 7/12 items
4 items - 33 points
We were placed 7th in picking.
evening was reception
There was this kid from UAE who must have been in 5th or 6th grade. He was asking the MIT team member what language his robot was programmed in and was noting it down in Arabic!
Day 5: July 3rd
Demo and media day
Each team had a 15 minute presentation. And there were a lot of people asking questions about sub-systems
Day 4: July 4th
Return to pittsburgh Just in time to catch the 4th of July fireworks!
Overall, it was awesome and we were very happy with our performance. We would like to thank John Dolan, Dimi and Maxim for their support throughout this competition.
Team HARP had a successful run! We would be handing over the project to the next year’s MRSD team
I’m sitting inside some really fancy hall inside the New York Public Library, I realize I have visited NYC thrice and spent more than a week but haven’t visited most places.
This library is breathtaking. Beautiful architecture. Wonderful place to sit and write stuff. It has the perfect ambience.
Never would have I thought I’d live just 6 hours away from Big Apple. Thanks to bus connectivity, it sorta feels like travelling overnight from Chennai to Trichy!
A major advantage of being based out of Pittsburgh is the proximity to many cities. Pittsburgh too has many meuseums and libraries I haven’t been to yet.
I’m migrating the site to the Jekyll static generator hosted on Github Pages. I wanted to give Jekyll a try as it’s much simpler to customize.