Robosphere is a bi-annual robotics workshop that focus on deploying robots into space for long-term operations. This includes adding robustness to existing robot platforms and making robots more and more self-sufficient such as being able to self-repair, perform habitat construction, utilize in-situ resources, and be more autonomous.
I wasn't around for last year's workshop, but this year it was at NASA Ames in Moffet Field, CA near San Jose. I live in Los Angeles, so we had decided to drive up which takes about 5.5 hours.
So three of my colleagues and I plus Prof. Wei-Min Shen gathered together at 5:30am and took a rental van up to San Jose. We stopped once to have some breakfast at some fast-food town, but we spent a lot of the time napping for the sleep we didn't get during the night. I'm not sure what we talked about, but I think we mostly did some joking around.
Finally, we arrived at NASA Ames at 11:15am. Only 3 hours and 15 minutes late! Sadly, we missed some of the speakers already who talked about habitat construction for extra-terrestrial environments. According to the program, I missed the following presentations:
- "Mobile lunar and planetary base architectures", Marc Cohen, NASA Ames Research Center
- "Mobitat: Mobile Modular Habitat", A. Scott Howe, Plug-in Creations Architecture
- "LB1 - A Case Study: A Lunar Habitat as a Self-sustaining Intelligent Robotic System", Susmita Mohanty, Moonfront LLC
- "Radiation and Micro-meteorite Shielded Lunar Habitat Formation by Semi-autonomous Robotic Excavation", Dr. Lyman Hazelton, KinetX Inc.
So the next section of talks was about "Robotic Colonies/Ecologies". These talks essentially boiled down to how to control many robots over a long period of time and have them adapt to the environment and needed tasks.
Anthony Enguirda of Griffith University in Australia started off by describing the concept of the robot colony and how it differs from the conventional paradigm. I arrived right in the middle of this talk, so I didn't learn very much. I'm looking at the accompanying paper in the proceedings, and it looks interesting, but it doesn't seem like there's a lot of substance. Of course a lot of this workshop was focused on wild speculation and the introduction of new ideas, so I think this is acceptable. I'll have to focus on this paper more closely when I have time.
Hamid Berenji of Intelligent Inference Systems Corp. gave a talk about Dynamic Cased-Based Reasoning (DCBR). This was a method for robots to ascertain their state and recover from faults and error conditions. This looked a lot like an expert system with the capability to generalize and adapt to the situation. This seems effective, but the drawback to any type of system like this is it requires a heck of a lot of pre-programming of all the fault cases you can think of.
Finally, Zhihua Qu of University of Central Florida gave a talk about a control-theoretic approach to controlling a large population of robots. It basically takes a huge matrix representing the state of every robot in the population and you add an extra row/column that is the human controller. Then you effect this matrix with your control inputs. It's a very interesting approach and I wonder how you could apply it. It seems in order for this control system to actually work, you need to know the state of all the robots and they need to receive your appropriate inputs. How do you do this in a physical space with poor communication, I don't know. Maybe there's an assumption in here that I didn't get.
After this, we went to lunch. More later.