Model integrated computing in robot control to synthesize real-time embedded code

Abstract

Manufacturing robots present a class of embedded systems with hard real-time constraints. On the one hand controller software has to satisfy tight timing constraints and rigorous memory requirements. Especially nonlinear dynamics and kinematics models are vital to modern model-based controllers and trajectory planning algorithms. Often this is still realized by manually coding and optimizing the software, a labor intensive and error-prone repetitive process. On the other hand shorter design-cycles and a growing number of customer-specific robots demand more flexibility not just in modeling. This paper presents a model-integrated computing approach to automated code synthesis of dynamics models that satisfies the harsh demands by including domain and problem specific constraints prescribed by the robotics application. It is shown that the use of such tailored formalisms leads to very efficient embedded software, competitive with the hand optimized alternative. At the same time it combines flexibility in model specification and usage with the potential for dynamic adaptation and reconfiguration of the model.