Rapid Trajectory Optimization Using C-FROST with Illustration on a Cassie-Series Dynamic Walking Biped

Ayonga Hereid, Omar Harib, Ross Hartley, Yukai Gong, Jessy W Grizzle
January 2019
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Abstract

One of the big attractions of low-dimensional models for gait design has been the ability to compute solutions rapidly, whereas one of their drawbacks has been the difficulty in mapping the solutions back to the target robot. This paper presents a set of tools for rapidly determining solutions for “humanoids” without removing or lumping degrees of freedom. The main tools are: (1) C-FROST, an open-source C++ interface for FROST, a direct collocation optimization tool; and (2) multi-threading. The results will be illustrated on a 20-DoF floating-base model for a Cassie-series bipedal robot through numerical optimization and physical experiments.

Type
Conference paper
Publication
IEEE/RSJ International Conference on Intelligent Robots and Systems
frost parallel optimization supervised learning
Ayonga Hereid
Ayonga Hereid
Assistant Professor of Mechanical Engineering

My research aims to develop computational and theoretical tools to mitigate the high dimensionality and nonlinearity present in robot control and motion planning problems.