This paper deals with online onboard behavior optimization for an autonomous mobile robot in the scope of the European FP7 Symbrion Project. The work presented here extends the (1+1)-online algorithm introduced in earlier publication. This algorithm is a variation of a famous Evolution Strategies adapted to autonomous robots. In this paper, we address a limitation of this algorithm regarding the ability to perform global search whenever a local optimum is reached. A new implementation of the algorithm, termed (1+1)-restart-online algorithm, is described and implemented within the Symbrion robotic Cortex M3 microcontroller. Results from the experiments show that the new algorithm is able to escape local optima and, as a consequence, converge faster and provides a richer set of relevant controllers.