1 citations · 2 across the 7 of their papers we have counts for
4 papers · 1 filter
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…
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…
Topological Exploration using Segmented Map with Keyframe Contribution in Subterranean Environments
Boseong Kim, Hyunki Seong, D. Hyunchul Shim
Existing exploration algorithms mainly generate frontiers using random sampling or motion primitive methods within a specific sensor range or search space. However, frontiers gener…
TempFuser: Learning Agile, Tactical, and Acrobatic Flight Maneuvers Using a Long Short-Term Temporal Fusion Transformer
Hyunki Seong, David Hyunchul Shim
Dogfighting is a challenging scenario in aerial applications that requires a comprehensive understanding of both strategic maneuvers and the aerodynamics of agile aircraft. The aer…