Hard materials machining is a recent technology focusing on materials in increasing use by automotive, aerospace, biomedical and other advanced industries. Insufficient rigidity and accuracy have been widely identified as the major hurdles preventing the adoption and widespread use of robots for metal-removal jobs, making robotic machining of hard materials quite difficult. To cope with these problems the robot industry has established new trends towards more rigid and precise robots, improving the robot accuracy by increasing structural stiffness (e.g. by using stiffer closed kinematic chains), by including calibration procedures and position mastering, as well as new sensing technologies by means of novel robot encoders in joints and external sensors. However, the achievable absolute accuracy so far within the range of 0.2 to 0.5 mm is still insufficient and approximately 20-100 times worst in comparison to the precise Computer-Numerical-Control (CNC) machines. Several research efforts recently address this problem trying to find new methods for precise robot material removal by using accurate external tracking sensors and high dynamic compensation mechanisms (e.g. active ultra-precise workpiece tables driven by piezo-electric actuators) to achieve accuracy comparable to that of CNC machines. However, such complex technical solutions that shift robotic systems positioning accuracy toward CNC machines also considerably increase the system costs and complexity to the level of production machines. By this means the cost saving potential by using industrial robots instead of CNC machines is considerably reduced. Despite of compensation or position errors, the critical chattering effects may further cause process inaccuracy, even instability and reduce tool or robot life-cycles. Moreover, such robotic systems appear not to be economic viable and practically reliable, especially for applications in SMEs and for small-batch high-variant production, which becomes a trade-mark of the European agile manufacturing.