A Framework for Adaptive and Goal Driven Behaviour Control of Multi robot Systems
Robot and multi robot systems are leaving the friendly well structured world of automation and are facing the challenges of a dynamic world. Such uncertain conditions call for a high degree of robustness and adaptivity for individual robots as well as for the organization of multi robot systems. This corresponds to the concepts of self adaptation and self organization. Robots adapting to the dynamic environment still have to pursue their given tasks or goals. In order to address the requirements of creating adaptive and goal driven multi robot systems, it is necessary to combine existing goal directed planning and decision making approaches with self adaptation and self organization mechanisms. This work addresses this challenge with a new hybrid approach integrated into a common robot framework, combining symbolic planning with reactive behaviour networks, machine learning, and the pattern based selection of suitable mechanisms. On that account it brings together the advantages of bottom up and top down oriented approaches.
2016 IEEE 1st International Workshops on Foundations and Applications of Self* Systems (FAS*W)