Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Marcucci, Tobia"'
Autor:
Graesdal, Bernhard Paus, Chia, Shao Yuan Chew, Marcucci, Tobia, Morozov, Savva, Amice, Alexandre, Parrilo, Pablo A., Tedrake, Russ
We present a novel method for global motion planning of robotic systems that interact with the environment through contacts. Our method directly handles the hybrid nature of such tasks using tools from convex optimization. We formulate the motion-pla
Externí odkaz:
http://arxiv.org/abs/2402.10312
Learning predictive models from observations using deep neural networks (DNNs) is a promising new approach to many real-world planning and control problems. However, common DNNs are too unstructured for effective planning, and current control methods
Externí odkaz:
http://arxiv.org/abs/2312.12791
Many computations in robotics can be dramatically accelerated if the robot configuration space is described as a collection of simple sets. For example, recently developed motion planners rely on a convex decomposition of the free space to design col
Externí odkaz:
http://arxiv.org/abs/2310.02875
Autor:
Ahn, Kwangjun, Pfrommer, Daniel, Umenberger, Jack, Marcucci, Tobia, Mhammedi, Zak, Jadbabaie, Ali
Statistical learning theory and high dimensional statistics have had a tremendous impact on Machine Learning theory and have impacted a variety of domains including systems and control theory. Over the past few years we have witnessed a variety of ap
Externí odkaz:
http://arxiv.org/abs/2306.01914
We present a fast algorithm for the design of smooth paths (or trajectories) that are constrained to lie in a collection of axis-aligned boxes. We consider the case where the number of these safe boxes is large, and basic preprocessing of them (such
Externí odkaz:
http://arxiv.org/abs/2305.01072
Trajectory optimization offers mature tools for motion planning in high-dimensional spaces under dynamic constraints. However, when facing complex configuration spaces, cluttered with obstacles, roboticists typically fall back to sampling-based plann
Externí odkaz:
http://arxiv.org/abs/2205.04422
Publikováno v:
SIAM Journal on Optimization, Vol. 34, No. 1, pp. 507-532, 2024
Given a graph, the shortest-path problem requires finding a sequence of edges with minimum cumulative length that connects a source vertex to a target vertex. We consider a variant of this classical problem in which the position of each vertex in the
Externí odkaz:
http://arxiv.org/abs/2101.11565
Autor:
Marcucci, Tobia, Tedrake, Russ
In hybrid Model Predictive Control (MPC), a Mixed-Integer Quadratic Program (MIQP) is solved at each sampling time to compute the optimal control action. Although these optimizations are generally very demanding, in MPC we expect consecutive problem
Externí odkaz:
http://arxiv.org/abs/1910.08251
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Akademický článek
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