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Calibration of robots has become a research field of great importance over the last decades especially in the field industrial robotics. The main reason for this is that the field of application was significantly broadened due to an increasing number of fully automated or robot assisted tasks to be performed. Those applications require significantly higher level of accuracy due to more delicate tasks that need to be fulfilled (e.g. assembly in the semiconductor industry or robot assisted medical surgery). In the past, (industrial) robot calibration had to be performed manually for every single robot under lab conditions in a long and cost intensive process. Expensive and complex measurement systems had to be operated by highly trained personnel. The result of this process is a set of measurements representing the robot pose in the task space (i.e. world coordinate system) and as joint encoder values. To determine the deviation, the robot pose indicated by the internal joint encoder values has to be compared to the physical pose (i.e. external measurement data). Hence, the errors in the kinematic model of the robot can be computed and therefore later on compensated. These errors are inevitable and caused by varying manufacturing tolerances and other sources of error (e.g. friction and deflection). They have to be compensated in order to achieve sufficient accuracy for the given tasks. Furthermore for performance, maintenance, or quality assurance reasons the robots may have to undergo the calibration process in constant time intervals to monitor and compensate e.g. ageing effects such as wear and tear. In modern production processes old fashioned procedures like the one mentioned above are no longer suitable. Therefore a new method has to be found that is less time consuming, more cost effective, and involves less (or in the long term even no) human interaction in the calibration process.
In its rather short history robotic research has come a long way in the half century since it started to exist as a noticeable scientic eld. Due to its roots in engineering, computer science, mathematics, and several other 'classical' scientic branches,a grand diversity of methodologies and approaches existed from the very beginning. Hence, the researchers in this eld are in particular used to adopting ideas that originate in other elds. As a fairly logical consequence of this, scientists tended to biology during the 1970s in order to nd approaches that are ideally adapted to the conditions of our natural environment. Doing so allows for introducing principles to robotics that have already shown their great potential by prevailing in a tough evolutionary selection process for millions of years. The variety of these approaches spans from efficient locomotion, to sensor processing methodologies and all the way to control architectures. Thus, the full spectrum of challenges for autonomous interaction with the surroundings while pursuing a task can be covered by such means. A feature that has proven to be amongst the most challenging to recreate is the human ability of biped locomotion. This is mainly caused by the fact that walking,running and so on are highly complex processes involving the need for energy efficient actuation, sophisticated control architectures and algorithms, and an elaborate mechanical design while at the same time posting restrictions concerning stability and weight. However, it is of special interest since our environment is favoring this specic kind of locomotion and thus promises to open up an enormous potential if mastered. More than the mere scientic interest, it is the fascination of understanding and recreating parts of oneself that drives the ongoing eorts in this area of research. The fact that this is not at all an easy task to tackle is not only caused by the highly dynamical processes but also has its roots in the challenging design process. That is because it cannot be limited to just one aspect like e.g. the control architecture, actuation, sensors, or mechanical design alone. Each aspect has to be incorporated into a sound general concept in order to allow for a successful outcome in the end. Since control is in this context inseparably coupled with the mechanics of the system, both has to be dealt with here.