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Contact-Implicit Trajectory Optimization for Dynamic Object Manipulation

Jean-Pierre Sleiman, Jan Carius, Ruben Grandia, Martin Wermelinger, Marco Hutter

Year
2019
Citations
20

Abstract

We present a reformulation of a contact-implicit optimization (CIO) approach that computes optimal trajectories for rigid-body systems in contact-rich settings.
\nA hard-contact model is assumed, and the unilateral constraints are imposed in the form of complementarity conditions. 
\nNewton's impact law is adopted for enhanced physical correctness.
\nThe optimal control problem is formulated as a multi-staged program through a multiple-shooting scheme. This problem structure is exploited within the FORCES Pro framework to retrieve optimal motion plans, contact sequences and control inputs with increased computational efficiency.
\nWe investigate our method on a variety of dynamic object manipulation tasks, performed by a six degrees of freedom robot. The dynamic feasibility of the optimal trajectories, as well as the repeatability and accuracy of the task-satisfaction are verified through simulations and real hardware experiments on one of the manipulation problems.

Keywords

CorrectnessComputer scienceTrajectory optimizationTrajectoryOptimal controlComplementarity (molecular biology)Object (grammar)Contact forceTask (project management)Variety (cybernetics)

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