2019
DOI: 10.1109/lra.2019.2900840
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Abstract: 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… Show more

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Cited by 50 publications
(33 citation statements)
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“…Future work will focus on systematic identification of parameters r n and r t and hardware validations. Another extension of the framework will focus on improving the numerical accuracy by using higher-order integration methods as in [33]. Fig.…”
Section: Discussionmentioning
confidence: 99%
“…Future work will focus on systematic identification of parameters r n and r t and hardware validations. Another extension of the framework will focus on improving the numerical accuracy by using higher-order integration methods as in [33]. Fig.…”
Section: Discussionmentioning
confidence: 99%
“…Moco and the direct collocation method have a number of limitations that should be considered when planning a simulation study. Moco currently lacks the ability to handle certain optimal control problems, such as those with multiple phases [ 45 ] or unilateral kinematic constraints [ 76 ]. Bringing custom model components (e.g., a fatigable muscle) into Moco requires knowledge of C++ and the OpenSim software architecture; future versions of the software should allow users to implement custom model components in MATLAB or Python.…”
Section: Availability and Future Directionsmentioning
confidence: 99%
“…1) Collocation: The trajectory is discretized into N 1 time periods (called finite elements) using polynomials. Each state trajectory is represented using a Runge-Kutta bases with Kcollocation points [34]. For these experiments, 3-point Radau (K = 3, with an accuracy of h 2K−1 [34]) was used to solve the differential equations, (1), at collocation points [34], [35].…”
Section: A Constraintsmentioning
confidence: 99%
“…Each state trajectory is represented using a Runge-Kutta bases with Kcollocation points [34]. For these experiments, 3-point Radau (K = 3, with an accuracy of h 2K−1 [34]) was used to solve the differential equations, (1), at collocation points [34], [35]. The time step between these finite elements is denoted h i and is constrained between the following bounds:…”
Section: A Constraintsmentioning
confidence: 99%