CHOMP: Covariant Hamiltonian Optimization for Motion Planning

Matthew Zucker, Nathan Ratliff, Anca Dragan, Mihail Pivtoraiko, Matthew Klingensmith, Christopher Dellin, J. Andrew (Drew) Bagnell, and Siddhartha Srinivasa
International Journal of Robotics Research, , May, 2013


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Abstract
In this paper, we present CHOMP (Covariant Hamiltonian Optimization for Motion Planning), a method for trajectory optimization invariant to reparametrization. CHOMP uses functional gradient techniques to iteratively improve the quality of an initial trajectory, optimizing a functional that trades off between a smoothness and an obstacle avoidance component. CHOMP can be used to locally optimize feasible trajectories, as well as to solve motion planning queries, converging to low- cost trajectories even when initialized with infeasible ones. It uses Hamiltonian Monte Carlo to alleviate the problem of convergence to high-cost local minima (and for probabilistic completeness), and is capable of respecting hard constraints along the trajectory. We present extensive experiments with CHOMP on manipulation and locomotion tasks, using 7-DOF manipulators and a rough-terrain quadruped robot.

Keywords
trajectory optimization, motion planning

Notes
Associated Center(s) / Consortia: Quality of Life Technology Center, National Robotics Engineering Center, and Center for the Foundations of Robotics
Associated Lab(s) / Group(s): Personal Robotics

Text Reference
Matthew Zucker, Nathan Ratliff, Anca Dragan, Mihail Pivtoraiko, Matthew Klingensmith, Christopher Dellin, J. Andrew (Drew) Bagnell, and Siddhartha Srinivasa, "CHOMP: Covariant Hamiltonian Optimization for Motion Planning," International Journal of Robotics Research, , May, 2013

BibTeX Reference
@article{Zucker_2013_7421,
   author = "Matthew Zucker and Nathan Ratliff and Anca Dragan and Mihail Pivtoraiko and Matthew Klingensmith and Christopher Dellin and J. Andrew (Drew) Bagnell and Siddhartha Srinivasa",
   title = "CHOMP: Covariant Hamiltonian Optimization for Motion Planning",
   journal = "International Journal of Robotics Research",
   month = "May",
   year = "2013",
}