Zobrazeno 1 - 10
of 795
pro vyhledávání: '"Ki, K."'
In this study, we address multi-robot localization issues, with a specific focus on cooperative localization and observability analysis of relative pose estimation. Cooperative localization involves enhancing each robot's information through a commun
Externí odkaz:
http://arxiv.org/abs/2401.15313
Aggressive Trajectory Tracking for Nano Quadrotors Using Embedded Nonlinear Model Predictive Control
This paper presents an aggressive trajectory tracking method for a small lightweight nano-quadrotor using nonlinear model predictive control (NMPC) based on acados. Controlling a nano quadrotor for accurate trajectory tracking at high speed in dynami
Externí odkaz:
http://arxiv.org/abs/2312.01015
Autor:
Kim, Sunwoo, Kim, Kwang-Ki K.
This paper presents model-based and model-free learning methods for economic and ecological adaptive cruise control (Eco-ACC) of connected and autonomous electric vehicles. For model-based optimal control of Eco-ACC, we considered longitudinal vehicl
Externí odkaz:
http://arxiv.org/abs/2312.01004
This paper presents a tutorial overview of path integral (PI) control approaches for stochastic optimal control and trajectory optimization. We concisely summarize the theoretical development of path integral control to compute a solution for stochas
Externí odkaz:
http://arxiv.org/abs/2309.12566
This paper considers the problem of managing single or multiple robots and proposes a cloud-based robot fleet manager, Adaptive Goal Management (AGM) System, for teams of unmanned mobile robots. The AGM system uses an adaptive goal execution approach
Externí odkaz:
http://arxiv.org/abs/2303.11535
Autor:
Kim, Min-Gyeom, Kim, Kwang-Ki K.
This study presents a hybrid trajectory optimization method that generates a collision-free smooth trajectory for autonomous mobile robots. The hybrid method combines sampling-based model predictive path integral (MPPI) control and gradient-based int
Externí odkaz:
http://arxiv.org/abs/2208.02439
Publikováno v:
IEEE Access, vol. 9, pages 103167-103183, 2021
This paper presents a vehicle speed planning system called the energy-optimal deceleration planning system (EDPS), which aims to maximize energy recuperation of regenerative braking of connected and autonomous electrified vehicles. A recuperation ene
Externí odkaz:
http://arxiv.org/abs/2102.07326
Publikováno v:
In Annual Reviews in Control 2024 57
Publikováno v:
In Journal of Energy Storage 30 November 2023 72 Part D
Autor:
Won Hyung Lee, Kwang-Ki K. Kim
Publikováno v:
IEEE Access, Vol 11, Pp 132766-132779 (2023)
This study presents two outlier-robust extended Kalman filtering (OREKF) methods for battery-state estimation. The first method is the auto-tuning (AT)-OREKF method, and the second is the expectation-maximization (EM)-OREKF method. The AT-OREKF is an
Externí odkaz:
https://doaj.org/article/7a30459d16834fe687078a3457e8e414