Contact-Implicit Trajectory Optimization using Orthogonal Collocation
This addresses the challenge of generating accurate, complex behaviors for robots with intermittent contact, though it appears incremental as it builds on existing methods.
The paper tackles the problem of poor accuracy in contact-implicit trajectory optimization for dynamic robots by combining orthogonal collocation with contact-implicit methods, resulting in significantly improved accuracy.
In this paper we propose a method to improve the accuracy of trajectory optimization for dynamic robots with intermittent contact by using orthogonal collocation. Until recently, most trajectory optimization methods for systems with contacts employ mode-scheduling, which requires an a priori knowledge of the contact order and thus cannot produce complex or non-intuitive behaviors. Contact-implicit trajectory optimization methods offer a solution to this by allowing the optimization to make or break contacts as needed, but thus far have suffered from poor accuracy. Here, we combine methods from direct collocation using higher order orthogonal polynomials with contact-implicit optimization to generate trajectories with significantly improved accuracy. The key insight is to increase the order of the polynomial representation while maintaining the assumption that impact occurs over the duration of one finite element.