most citedGame-Theoretic Model Predictive Control with Data-Driven Identification of Vehicle Model for Head-to-Head Autonomous Racing

16 citations · 21 across the 4 of their papers we have counts for

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5 papers · 1 filter

cs.RO20223 cited

Design, Field Evaluation, and Traffic Analysis of a Competitive Autonomous Driving Model in a Congested Environment

Daegyu Lee, Hyunki Seong, Seungil Han +3

Recently, numerous studies have investigated cooperative traffic systems using the communication among vehicle-to-everything (V2X). Unfortunately, when multiple autonomous vehicles…

cs.RO20211 cited

Mapless Navigation: Learning UAVs Motion forExploration of Unknown Environments

Sunggoo Jung, David Hyunchul Shim

This study presents a new methodology for learning-based motion planning for autonomous exploration using aerial robots. Through the reinforcement learning method of learning throu…

cs.RO202116 cited

Game-Theoretic Model Predictive Control with Data-Driven Identification of Vehicle Model for Head-to-Head Autonomous Racing

Chanyoung Jung, Seungwook Lee, Hyunki Seong +2

Resolving edge-cases in autonomous driving, head-to-head autonomous racing is getting a lot of attention from the industry and academia. In this study, we propose a game-theoretic…

cs.RO2021

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…

cs.RO20211 cited

BAXTER: Bi-modal Aerial-Terrestrial Hybrid Vehicle for Long-endurance Versatile Mobility: Preprint Version

Hyungho Chris Choi, Inhwan Wee, Micah Corah +5

Unmanned aerial vehicles are rapidly evolving within the field of robotics. However, their performance is often limited by payload capacity, operational time, and robustness to imp…