119 citations · 185 across the 8 of their papers we have counts for
9 papers
Top-Quark Mass Scheme Uncertainties in Higgs Boson Pair Production via Gluon Fusion
Clara Del Pio, Sebastian Jaśkiewicz, Rebecca von Kuk +1
We investigate theoretical uncertainties arising from the choice of the top-quark mass scheme in Higgs boson pair production via gluon fusion. First, we implement the resummation o…
Deep Learning Warm Starts for Trajectory Optimization on the International Space Station
Somrita Banerjee, Abhishek Cauligi, Marco Pavone
Trajectory optimization is a cornerstone of modern robot autonomy, enabling systems to compute trajectories and controls in real-time while respecting safety and physical constrain…
ShadowNav: Autonomous Global Localization for Lunar Navigation in Darkness
Deegan Atha, R. Michael Swan, Abhishek Cauligi +5
The ability to determine the pose of a rover in an inertial frame autonomously is a crucial capability necessary for the next generation of surface rover missions on other planetar…
ShadowNav: Crater-Based Localization for Nighttime and Permanently Shadowed Region Lunar Navigation
Abhishek Cauligi, R. Michael Swan, Masahiro Ono +4
There has been an increase in interest in missions that drive significantly longer distances per day than what has currently been performed. Further, some of these proposed mission…
CoCo: Online Mixed-Integer Control via Supervised Learning
A. Cauligi, P. Culbertson, E. Schmerling +3
Many robotics problems, from robot motion planning to object manipulation, can be modeled as mixed-integer convex programs (MICPs). However, state-of-the-art algorithms are still u…
NeBula: Quest for Robotic Autonomy in Challenging Environments; TEAM CoSTAR at the DARPA Subterranean Challenge
Ali Agha, Kyohei Otsu, Benjamin Morrell +69
This paper presents and discusses algorithms, hardware, and software architecture developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), competing in the DARP…
Learning Mixed-Integer Convex Optimization Strategies for Robot Planning and Control
A. Cauligi, P. Culbertson, B. Stellato +3
Mixed-integer convex programming (MICP) has seen significant algorithmic and hardware improvements with several orders of magnitude solve time speedups compared to 25 years ago. De…
Trajectory Optimization on Manifolds: A Theoretically-Guaranteed Embedded Sequential Convex Programming Approach
Riccardo Bonalli, Andrew Bylard, Abhishek Cauligi +2
Sequential Convex Programming (SCP) has recently gained popularity as a tool for trajectory optimization due to its sound theoretical properties and practical performance. Yet, mos…
GuSTO: Guaranteed Sequential Trajectory Optimization via Sequential Convex Programming
Riccardo Bonalli, Abhishek Cauligi, Andrew Bylard +1
Sequential Convex Programming (SCP) has recently seen a surge of interest as a tool for trajectory optimization. However, most available methods lack rigorous performance guarantee…