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Mar, 2025
一种简单的约束意识模仿学习方法及其在自主赛车中的应用
A Simple Approach to Constraint-Aware Imitation Learning with Application to Autonomous Racing
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Shengfan Cao, Eunhyek Joa, Francesco Borrelli
TL;DR
本研究解决了模仿学习中约束满足的难题，尤其是在靠近系统处理极限的任务中。我们提出了一种简单的方法，将安全性纳入模仿学习目标，并通过自主赛车任务的模拟验证了该方法的有效性，显示出相比基线方法更好的约束满足率和任务表现一致性。
Abstract
Guaranteeing
Constraint Satisfaction
is challenging in
Imitation Learning
(IL), particularly in tasks that require operating near a system's handling limits. Traditional IL methods often struggle to enforce const
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