Everett Yang

I am a rising senior CS major from Texas A&M University working in Nancy Amato's robot motion planning lab.

Week 1

This week was mainly about setting up the computers James and I brought from A&M and settling into the new lab and the new town. We had Glen help us with installing the dependencies and connecting the computers to the Illinois server.

I read (and am reading) some papers related to manipulator planning under constraints to try to achieve a deeper understanding of the problem. Specifically, I've been looking for past algorithms that provide a general solution to this problem.

Here are a list of papers I am reading:
1. Manipulation Planning with Probabilistic Roadmaps by Simeon et al.
2. Trajectory Planning for Manipulators Operating in Confined Workspaces by Kabir et al.
3. A constraint-based method for solving sequential manipulation planning problems by Lozano-Perez et al.

The first one of the list is particularly interesting and helpful because they provide a clear definition of the constraint problem and a general solution to it. I plan to read the details later.

I spent a good chunk of Thursday and Friday getting PMPL set up and helping other students. I ran into some annoying bugs that Diane helped me with.

We had a group meeting for the first lesson of the crash course on Friday. Diane did a good job explaining all of the basic concepts.

I plan to turn my thesis work into a publishable paper. I will collect more data and present a more solid contribution (the contribution is a bit shaky right now). In addition, I will try to brainstorm some original ideas for constrained manipulator planning in general.

Week 2:

I had a report here now its gone.

Week 3:

I'm trying to implement a fixed based multi-armed example to demonstrate my reachable volume algorithm. I'm having trouble figuring out how to deal with two different manipulators in the same problem. I need to be able to compute their reachable volume intersection so that I can figure out if one context has a transition point with another, but I can't seem to find the right tools in PMPL to do so. The most relevant thing I can find is the GroupCfg framework. But that also isn't exactly what I want because I don't want to calculate the reachable volume of the system, just each individual arm. Hopefully I can figure something out next week.

I'll send a more detailed plan for the paper tomorrow.

I also have some skeleton code for the RV local planner set up. So I will also work on finishing that next week.

I helped Felipe with his discrete environment strategy. I suggested a way for him to build some contrived graph and also helped him manually choose his start and goal from the same graph after it is built. It didn't take so long because everything was essentially hard-coded (which isn't ideal but he insisted that is what he needed).

The lab went out to Joe's on Thursday for burgers and a couple games of bean bags. It was fun.

Week 4:

made progress in the RV stepping and local planning code this week. I have a base implementation for the local planner and the stepping function that compiles.

However, there are a few things left to figure out in order for the local planner implementation to work:

1. Implement a function to check whether a point is inside a RV intersection (for RV stepping). Right now we only have a function for randomly generating a point in the intersection.
2. Generalize the above to handle arbitrary number of intersections. (This is probably not an immediate concern).
3. Make sure the "parent" chains are what I think they are in the literature. Right now I am just breaking the big chain into two smaller chains that meet at the joint to be stepped. Not sure if this is correct. This also affects the "neighboring" joint calculation.

Also, I am making a few functions in the ReachableVolumeSampler static in order to reuse the code in the planner. Not sure if this is ideal.

After I get the local planner working (presumably next week if all goes well), I will run some pick and place examples, first with the simple manipulator then hopefully with the Kuka. I am thinking of running such examples by:

1. Giving two end effector constraints
2. Sampling nodes that satisfy these two constraints.
3. Use the local planner to incrementally step nodes from the first constraint (pick up point) in the list to the second constraint (drop off point).

A concern of mine is that I am not quite sure how far we should go for the ICRA paper. I was thinking that the algorithm should be general enough to automatically detect transitions between contexts (and so this could be the proposed novelty), but it seems this isn't really needed since the constraints and their ordering in the problem are both given in many scenarios. Then I am left to think that we need only more examples (specifically ones with end effector constraints) on top of the one in my thesis and that the novelty is in the way we sample from the set of given ordered constraints (done in my thesis).

I continued to help Felipe with whatever questions he had this week. It seems he is more comfortable with the library now.

It seems I will be presenting my research at MAA MathFest this year once again. Like last year, the math department and MAA is covering all the costs and perhaps even more. The conference is in Cincinnati this year, so pretty close. There are a few others from TAMU going as well.