Shadow Program Inversion with Differentiable Planning: A Framework for Unified Robot Program Parameter and Trajectory Optimization
Benjamin Alt, Claudius Kienle, Darko Katić, Rainer Jäkel, Michael Beetz · 2025
This paper presents Shadow Program Inversion with Differentiable Planning (SPI-DP), a novel first-order optimizer capable of optimizing robot programs with respect to both high-level task objectives and motion-level constraints. To that end, we introduce Differentiable Gaussian Process Motion Planning for N-DoF Manipulators (dGPMP2-ND), a differentiable collision-free motion planner for serial N-DoF kinematics, and integrate it into an iterative, gradient-based optimization approach for generic, parameterized robot program representations. SPI-DP allows first-order optimization of planned trajectories and program parameters with respect to objectives such as cycle time or smoothness subject to e.g. collision constraints, while enabling humans to understand, modify or even certify the optimized programs. We provide a comprehensive evaluation on two practical household and industrial applications.