Intelligent approaches in locomotion

In this paper we review more than 50 publications and try to not only give a snap shot of the current state of the art research in the area, but also to critically analyse and compare different methodologies used in this research field. Among the investigated intelligent approaches for solving locomotion problems are Neural Networks, Hidden Markov models, Rule Based and Fuzzy Logic systems, as well as Analytical concepts. We try to compare those methods based on the quality of the produced solutions in terms of time, stability, correctness and the expense and cost for achieving them. At the end of each section we list the advantages and disadvantages of the reviewed methods and scrutinise them considering the complexity of the approaches, their applicability to the investigated locomotion tasks and the constraints of the produced solutions.