Task-space trajectories via cubic spline optimization

Authors:
J. Zico Kolter;Andrew Y. Ng
Affiliations:
Computer Science Department, Stanford University, Stanford, CA;Computer Science Department, Stanford University, Stanford, CA
Venue:
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Year:
2009

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Abstract

We consider the task of planning smooth trajectories for robot motion. In this paper we make two contributions. First we present a method for cubic spline optimization; this technique lets us simultaneously plan optimal task-space trajectories and fit cubic splines to the trajectories, while obeying many of the same constraints imposed by a typical motion planning algorithm. The method uses convex optimization techniques, and is therefore very fast and suitable for real-time re-planning and control. Second, we apply this approach to the tasks of planning foot and body trajectory for a quadruped robot, the "LittleDog," and show that the proposed approach improves over previous work on this robot.