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Contact-Implicit Trajectory Optimization for planning out-of-the-box contact-interaction trajectories.

This package provides a generalized solution for planning dynamic contact-interaction trajectories. The software package leverages existing open-source code for [Contact Implicit Trajectory Optimization]( based on a variable smooth contact model and a successive convexification algorithm for the trajectory optimization. This software package adds a penalty loop that adjusts the penalty on the virtual forces automatically and a post-process stage that improves solutions through a forward pass by exploiting the contact information implied by the utilization of the virtual forces.

Underactuated dynamics with frictional rigid-body contacts is modeled using [MuJoCo]( The convex subproblems in trajectory optimization are solved by the sparse quadratic programming solver [SQOPT]( The distance between collision geometries is calculated using [FCL]( The input to the planner is an XML model of the environment including the geometric, frictional, and mass properties of the bodies as well as geometric sites representing contact candidates to be used in the variable smooth contact model. The model file, the index and the desired configuration of the free body of interest, and pairs of contact candidates are modified through the parameters file 'config/params.yaml'.

  •  Onol, A.O., Corcodel, R., Long, P., Padir, T., "Tuning-Free Contact-Implicit Trajectory Optimization", IEEE International Conference on Robotics and Automation (ICRA), DOI: 10.1109/​ICRA40945.2020.9196805, May 2020, pp. 1183-1189.
    BibTeX TR2020-065 PDF Video Software
    • @inproceedings{Onol2020may,
    • author = {Onol, Aykut O. and Corcodel, Radu and Long, Philip and Padir, Taskin},
    • title = {Tuning-Free Contact-Implicit Trajectory Optimization},
    • booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
    • year = 2020,
    • pages = {1183--1189},
    • month = may,
    • publisher = {IEEE},
    • doi = {10.1109/ICRA40945.2020.9196805},
    • issn = {2577-087X},
    • isbn = {978-1-7281-7395-5},
    • url = {}
    • }

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