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Found 5 papers, 1 papers with code
Federated Multi-Agent Mapping for Planetary Exploration
In multi-agent robotic exploration, managing and effectively utilizing the vast, heterogeneous data generated from dynamic environments poses a significant challenge.
Improving Computational Efficiency for Powered Descent Guidance via Transformer-based Tight Constraint Prediction
T-PDG uses data from prior runs of trajectory optimization algorithms to train a transformer neural network, which accurately predicts the relationship between problem parameters and the globally optimal solution for the powered descent guidance problem.
ShadowNav: Crater-Based Localization for Nighttime and Permanently Shadowed Region Lunar Navigation
This GITL operation limits the distance that can be driven in a day to a few hundred meters, which is the distance that the rover can maintain acceptable localization error via relative methods.
NeBula: Quest for Robotic Autonomy in Challenging Environments; TEAM CoSTAR at the DARPA Subterranean Challenge
This paper presents and discusses algorithms, hardware, and software architecture developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), competing in the DARPA Subterranean Challenge.
CoCo: Learning Strategies for Online Mixed-Integer Control
Mixed-integer convex programming (MICP) is a popular modeling framework for solving discrete and combinatorial optimization problems arising in various settings.
