This webinar introduces new techniques and case studies for efficiently increasing the fidelity of system models for multibody robotic system design. Using symbolic computation techniques, multibody models can be effectively preprocessed to select optimal coordinate frames, eliminate redundant calculations, simplify algebraic constraints, and generate computationally minimal code for real-time deployment. Furthermore, novel mathematical techniques can be deployed for efficient parameter optimization and other advanced analysis.
Applications in robotics, including space and industrial robotics will be presented. The symbolic computation system Maple and the related modeling system MapleSim will be used to illustrate examples.
Attend this webinar to learn:
— How symbolic formulations can increase simulation speed without reducing model fidelity
— How high fidelity models can accelerate design time, reduce costly design errors, and ultimately improve the functional performance of robotics systems