1 citations · 2 across the 7 of their papers we have counts for
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cs.RO2024
Learning from Demonstration with Hierarchical Policy Abstractions Toward High-Performance and Courteous Autonomous Racing
Chanyoung Chung, Hyunki Seong, David Hyunchul Shim
Fully autonomous racing demands not only high-speed driving but also fair and courteous maneuvers. In this paper, we propose an autonomous racing framework that learns complex raci…
cs.LG2024★ 1 cited
Self-Supervised Interpretable End-to-End Learning via Latent Functional Modularity
Hyunki Seong, David Hyunchul Shim
We introduce MoNet, a novel functionally modular network for self-supervised and interpretable end-to-end learning. By leveraging its functional modularity with a latent-guided con…
cs.RO2024
Skill Q-Network: Learning Adaptive Skill Ensemble for Mapless Navigation in Unknown Environments
Hyunki Seong, David Hyunchul Shim
This paper focuses on the acquisition of mapless navigation skills within unknown environments. We introduce the Skill Q-Network (SQN), a novel reinforcement learning method featur…