Shadow Program Inversion with Differentiable Planning: A Framework for Unified Robot Program Parameter and Trajectory Optimization

This paper presents 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 DGPMP2-ND, a differentiable collision-free motion planner for serial N-DoF kinematics, and integrate...

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Bibliographic Details
Published in:arXiv.org 2024-09
Main Authors: Alt, Benjamin, Kienle, Claudius, Katic, Darko, Jäkel, Rainer, Beetz, Michael
Format: Article
Language:English
Subjects:
Collision avoidance
Constraints
Cycle time
Industrial applications
Kinematics
Motion planning
Parameter modification
Robot dynamics
Smoothness
Trajectory optimization
Trajectory planning
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Summary:This paper presents 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 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.
ISSN:2331-8422