Zobrazeno 1 - 10
of 158
pro vyhledávání: '"Mac Schwager"'
Autor:
Simon Le Cleac'h, Mac Schwager, Zachary Manchester, Vikas Sindhwani, Pete Florence, Sumeet Singh
Publikováno v:
IEEE Robotics and Automation Letters. 8:4012-4019
We present a differentiable formulation of rigid-body contact dynamics for objects and robots represented as compositions of convex primitives. Existing optimization-based approaches simulating contact between convex primitives rely on a bilevel form
Autor:
Simon Le Cleac'h, Hong-Xing Yu, Michelle Guo, Taylor Howell, Ruohan Gao, Jiajun Wu, Zachary Manchester, Mac Schwager
Publikováno v:
IEEE Robotics and Automation Letters. 8:2780-2787
We present a differentiable pipeline for simulating the motion of objects that represent their geometry as a continuous density field parameterized as a deep network. This includes Neural Radiance Fields (NeRFs), and other related models. From the de
Publikováno v:
IEEE Transactions on Robotics. :1-15
Publikováno v:
IEEE Transactions on Robotics. :1-20
Autor:
Ola Shorinwa, Mac Schwager
Publikováno v:
IEEE Transactions on Automatic Control. :1-16
Autor:
Ravi Haksar, Mac Schwager
Publikováno v:
IEEE Transactions on Automatic Control. :1-16
Autor:
Ravi N. Haksar, Mac Schwager
Publikováno v:
IEEE Transactions on Control of Network Systems. 9:1447-1458
Publikováno v:
Field Robotics. 2:1971-1998
Autonomous survey and aerial photogrammetry applications require solving a path planning problem that ensures sensor coverage over a specified area. In this work, we provide a multi-robot path planning method that can obtain this coverage over an arb
Publikováno v:
IEEE Transactions on Robotics. 37:1906-1920
In this work, we consider a group of robots working together to manipulate a rigid object to track a desired trajectory in $\text{SE}(3)$ . The robots do not know the mass or friction properties of the object, or where they are attached to the object
Publikováno v:
IEEE Transactions on Robotics. 37:1313-1325
In this article, we propose a nonlinear receding horizon game-theoretic planner for autonomous cars in competitive scenarios with other cars. The online planner is specifically formulated for a multiple-car autonomous racing game, in which each car t