Task-based Limb Optimization for Legged Robots


Sehoon Ha (Disney Research Pittsburgh)
Stelian Coros (Carnegie Mellon University)
Alexander Alspach (Disney Research Pittsburgh)
Joohyung Kim (Disney Research Los Angeles)
Katsu Yamane (Disney Research Pittsburgh)

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2016

October 11, 2016


The design of legged robots is often inspired by animals evolved to excel at different tasks. However, while mimicking morphological features seen in nature can be very powerful, robots may need to perform motor tasks that their living counterparts do not. In the absence of designs that can be mimicked, an alternative is to resort to mathematical models that allow the relationship between a robot’s form and function to be explored. In this paper, we propose such a model to codesign the motion and leg configurations of a robot such that a measure of performance is optimized. The framework begins by planning trajectories for a simplified model consisting of the center of mass and feet. The framework then optimizes the length of each leg link while solving for associated full-body motions. Our model was successfully used to find optimized designs for legged robots performing tasks that include jumping, walking, and climbing up a step. Although our results are preliminary and our analysis makes a number of simplifying assumptions, our findings indicate that the cost function, the sum of squared joint torques over the duration of a task, varies substantially as the design parameters change.

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