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Using a bottom‐up, model‐free approach when building robots is often seen as a less scientific way, compared to a top‐down model‐based approach, because the results are not easily generalizable to other systems. The authors, however, hypothesize that this problem may be addressed by using solid experimental methods. The purpose of this paper is to show how well‐known experimental methods from bio‐mechanics are used to measure and locate weaknesses in a bottom‐up, model‐free implementation of a quadruped walker and come up with a better solution.

To study the bottom‐up, mode‐free approach, the authors used the robotic construction kit, LocoKit. This construction kit allows researchers to construct legged robots, without having a mathematical model beforehand. The authors used no specific mathematical model to design the robot, but instead used intuition and took inspiration from biology. The results were afterwards compared with results gained from biology, to see if the robot has some of the key elements the authors were looking for.

With the use of LocoKit as the experimental platform, combined with known experimental measurement methods from biology, the authors have shown how a bottom‐up, model‐free design approach can be used to gain specific knowledge on a robotic platform, and also how knowledge can potentially be generalized from this approach.

This paper shows that even though a bottom‐up, model‐free approach was taken, the results can still be compared with results from, for example, biology, because solid experimental methods were used.