Researching Adaptive Robot Behaviors in a Simulation Environment
We have a team of contributors that have been working together to extend the environment to research strategies for autonomously adapting behaviors in a robot simulation. This project will extend that effort to investigate more complex and hopefully more dynamically adaptive behaviors.
The long-term results could apply to any type of complex adaptive system, not only robots, but also including adaptations in other future systems such as the Smart Grid, robots in healthcare systems, military, and smart manufacturing systems.
There many opportunities to learn new things related to simulation environments, dynamic behavior adaptation, robots and agent-based systems, conducting experiments, and tradeoff analysis.
Robots in the not too distant future will need to autonomously adapt to deal with changing situations, such as adapting to failure situations or changes in the environment. Robots will be self-aware of their environment, and be able to self-protect, self-heal, and self-optimize.
The following describes the key project activities:
1) Plan to research dynamically creating adaptive behaviors for robots
2) Use a simulation environment that runs dynamically adapting robots
3) Conduct experiment with different behavioral adaptation strategies and measure the results
4) Perform an analysis of the experimental results to assess the most promising strategies
5) Document the results in conference-ready paper
6) Recommend or assist in improving the experimentation environment
M. Blackburn, J. Malave, B. Phillips, A. Platt, Using Bayesian-based Behavioral Adaptation Strategies to Support Runtime Verification of Self-Adapting Systems, International Conference on Self-Adaptive and Self-Organizing Systems, 2013.
B. Cheng, Rogério L. Giese, P. Inverardi, J. Magee, J. Andersson, B. Becker, N. Bencomo, Y. Brun, B. Cukic, G. Serugendo, S. Dustdar, A. Finkelstein, C. Gacek, K. Geihs, V. Grassi, G. Karsai, H. Kienle, J. Kramer, M. Litoiu, S. Malek, R. Mirandola, H. Müller, S. Park, M. Shaw, M. Tichy, M. Tivoli, D. Weyns, J. Whittle, Software Engineering for Self-Adaptive Systems: A Research Roadmap, Software Engineering for Self-Adaptive Systems, Springer-Verlag, Berlin, Heidelberg, 2009.
M. Salehie, L. Tahvildari, Self-adaptive software: Landscape and research challenges. ACM Trans. Auton. Adapt. Syst. 4, 14:1–14:42 (May 2009), http://doi.acm.org/10.1145/1516533.1516538, 96.
There are no requirements as there are many different ways students can support this effort.